Overview The Research Software Engineering (RSE) Group, located institutionally in Princeton Research Computing but extending across campus, is hiring an Associate Director of Research Software Engineering. You will report to the Sr. Director of Research Software Engineering. The RSE Group collectively provides computational research expertise to nearly every division at Princeton: Engineering and Applied Science, Humanities, Social Sciences, and Natural Sciences. The RSE group is a centralized team of software experts focused on improving the quality, performance, and sustainability of Princeton's computational research software. The group is committed to building collaborative environments that value the best software engineering practices for sharing and applying cross-disciplinary computational techniques in new and emerging areas. In this position, you will build and lead a growing team of Research Software Engineers who provide dedicated expertise to researchers to create the most efficient, scalable, and sustainable research code possible to enable new scientific and scholarly advances. You will have the opportunity, and be encouraged, to bring new initiatives, technologies, and/or approaches to the RSE group and Princeton Research Software Community. You will develop strong relationships with new research groups to understand and assess their research software needs, determine the appropriate RSE support model, and work to match or recruit researchers with the right competencies and fit to a project. You'll act as a liaison to departments, overseeing the work of several research software engineers, making sure that each project is benefiting appropriately from the research collaboration and addressing, troubleshooting, or problem-solving any barriers or roadblocks with RSEs. You will oversee and encourage the professional development of the research software engineers you manage by engaging with the broader research community, and encouraging and enabling their participation in the boarder University research mission via training workshops, advising, consultation, curricular support, and/or participating in conferences or research groups outside of their immediate team. Finally, as part of the RSE management team, you will contribute to the strategic vision and mission for Research Software Engineering at Princeton. If you have a background in research software development and experience leading teams, you are poised to make an immediate impact on the research software engineering landscape at Princeton. You will collaborate closely with colleagues in Research Computing as well as with leading faculty researchers, student researchers, and technical staff in University departments, national labs, and industry. This role functions within a dynamic, supportive team environment that permits diverse backgrounds to thrive, including those wanting to make a career change and those with non-traditional career tracks, educational paths, or life experiences. If this environment sounds like a strong match, or even an exciting challenge, we encourage you to apply and use your cover letter to explain why you would be a good fit for the role. Responsibilities Technical Leadership Bring creativity, foresight, and mature professional judgment in anticipating and solving unprecedented problems, determining project objectives and requirements, and developing standards and guides for diverse software engineering, computing, and scientific/scholarly activities. Pursue and lead new synergistic initiatives that advance the RSE group and Princeton research software community. Initiate, structure, and schedule regular code reviews and other group technical activities for the RSE group. Mentor and provide technical leadership to members of the Research Software Engineering team. Maintain knowledge of current software development tools, techniques, and programming languages. Follow trends in software development and software management. Suggest transdisciplinary collaboration when appropriate Provide guidance to research teams as they pursue external funding, especially for units that are not normally supported by sponsored research. Management Collaboratively establish project priorities for RSE teams and follow best practices in project management. Determine staffing models for a variety of research needs in conversation and collaboration with the Senior Director and RSE advisory committee. Communicate with and facilitate communication between PIs, stakeholders, and the RSE group. Develop criteria for success, monitor and review progress at regular intervals, and manage expectations within and among diverse stakeholders. Manage effort and oversee the computational work of the RSE team through direct and matrix reporting structures. Conduct Annual Performance Reviews for RSE staff in collaboration with other supervisors. Write job descriptions and work directly with HR on recruitment and retention. Assist in building and developing a diverse, effective, and collaborative group of Research Software Engineers. Create an inclusive atmosphere and environment in which best engineering practices are valued, shared, and prioritized. Supervise professional development of direct reports, including the coordination of activities and events supporting the acquisition of new skills and expertise. Department outreach and collaboration Initiate and maintain extensive contact with key researchers, scientists, and scholars within a wide range of research groups and skillfully removes barriers to successful RSE collaborations. Engage and build relationships with a multitude of researchers, academic departments, and institutes/centers that partner with the RSE program. Create new relationships with academic departments and researchers to promote the benefits of collaborative research with an RSE. Oversee creation and promotion of domain-specific support structures and promotes a culture of best practices in collaborative research among collaborators within a variety of settings and domains. Initiate and maintain contact with colleagues within Research Computing and the broader Princeton computing community to effectively grow and develop software engineering capabilities. Strategic Vision for RSE Contribute to the strategic vision for Research Software Engineering (RSE) at Princeton, as well as contribute to national and international efforts to drive the direction of the RSE profession. Qualifications 7-10 years of some combination of the following: Software development (preferably in a research environment) Supporting computational research and software development in an academic setting Leading a software development team in a research environment that had multiple stakeholders 3-5 years of experience managing people, projects, and/or resources. Demonstrably strong programming skills, particularly in the languages common in research software applications. E.g. Python, C/C++, Fortran, R, MATLAB, and/or Julia. Openly value and espouse software engineering and development activities including requirements analysis, design, implementation, testing, deployment, and maintenance. Exceptional written/oral/interpersonal communication skills, both with regard to technical and non-technical audiences. Excellent organizational and project management skills; ability to prioritize and manage multiple complex initiatives and projects serving various research groups with available resources; ability to respond quickly to changing business needs and priorities. Ability to lead a team of highly competent professionals with varying backgrounds, reporting lines, and responsibilities. Must be a strong mentor and developer of people. Proactive approach to seeking information and ideas from peers, supervisors, and project partners. Education: A bachelor's degree is required. A Masters/Ph.D. is strongly preferred. PREFERRED Strong research background in computational science or engineering, computational social science, and/or digital humanities. Knowledge of Machine Learning or large AI models. Research Software Engineering experience. Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. KNOW YOUR RIGHTS PI21b1ee1-
04/29/2024
Full time
Overview The Research Software Engineering (RSE) Group, located institutionally in Princeton Research Computing but extending across campus, is hiring an Associate Director of Research Software Engineering. You will report to the Sr. Director of Research Software Engineering. The RSE Group collectively provides computational research expertise to nearly every division at Princeton: Engineering and Applied Science, Humanities, Social Sciences, and Natural Sciences. The RSE group is a centralized team of software experts focused on improving the quality, performance, and sustainability of Princeton's computational research software. The group is committed to building collaborative environments that value the best software engineering practices for sharing and applying cross-disciplinary computational techniques in new and emerging areas. In this position, you will build and lead a growing team of Research Software Engineers who provide dedicated expertise to researchers to create the most efficient, scalable, and sustainable research code possible to enable new scientific and scholarly advances. You will have the opportunity, and be encouraged, to bring new initiatives, technologies, and/or approaches to the RSE group and Princeton Research Software Community. You will develop strong relationships with new research groups to understand and assess their research software needs, determine the appropriate RSE support model, and work to match or recruit researchers with the right competencies and fit to a project. You'll act as a liaison to departments, overseeing the work of several research software engineers, making sure that each project is benefiting appropriately from the research collaboration and addressing, troubleshooting, or problem-solving any barriers or roadblocks with RSEs. You will oversee and encourage the professional development of the research software engineers you manage by engaging with the broader research community, and encouraging and enabling their participation in the boarder University research mission via training workshops, advising, consultation, curricular support, and/or participating in conferences or research groups outside of their immediate team. Finally, as part of the RSE management team, you will contribute to the strategic vision and mission for Research Software Engineering at Princeton. If you have a background in research software development and experience leading teams, you are poised to make an immediate impact on the research software engineering landscape at Princeton. You will collaborate closely with colleagues in Research Computing as well as with leading faculty researchers, student researchers, and technical staff in University departments, national labs, and industry. This role functions within a dynamic, supportive team environment that permits diverse backgrounds to thrive, including those wanting to make a career change and those with non-traditional career tracks, educational paths, or life experiences. If this environment sounds like a strong match, or even an exciting challenge, we encourage you to apply and use your cover letter to explain why you would be a good fit for the role. Responsibilities Technical Leadership Bring creativity, foresight, and mature professional judgment in anticipating and solving unprecedented problems, determining project objectives and requirements, and developing standards and guides for diverse software engineering, computing, and scientific/scholarly activities. Pursue and lead new synergistic initiatives that advance the RSE group and Princeton research software community. Initiate, structure, and schedule regular code reviews and other group technical activities for the RSE group. Mentor and provide technical leadership to members of the Research Software Engineering team. Maintain knowledge of current software development tools, techniques, and programming languages. Follow trends in software development and software management. Suggest transdisciplinary collaboration when appropriate Provide guidance to research teams as they pursue external funding, especially for units that are not normally supported by sponsored research. Management Collaboratively establish project priorities for RSE teams and follow best practices in project management. Determine staffing models for a variety of research needs in conversation and collaboration with the Senior Director and RSE advisory committee. Communicate with and facilitate communication between PIs, stakeholders, and the RSE group. Develop criteria for success, monitor and review progress at regular intervals, and manage expectations within and among diverse stakeholders. Manage effort and oversee the computational work of the RSE team through direct and matrix reporting structures. Conduct Annual Performance Reviews for RSE staff in collaboration with other supervisors. Write job descriptions and work directly with HR on recruitment and retention. Assist in building and developing a diverse, effective, and collaborative group of Research Software Engineers. Create an inclusive atmosphere and environment in which best engineering practices are valued, shared, and prioritized. Supervise professional development of direct reports, including the coordination of activities and events supporting the acquisition of new skills and expertise. Department outreach and collaboration Initiate and maintain extensive contact with key researchers, scientists, and scholars within a wide range of research groups and skillfully removes barriers to successful RSE collaborations. Engage and build relationships with a multitude of researchers, academic departments, and institutes/centers that partner with the RSE program. Create new relationships with academic departments and researchers to promote the benefits of collaborative research with an RSE. Oversee creation and promotion of domain-specific support structures and promotes a culture of best practices in collaborative research among collaborators within a variety of settings and domains. Initiate and maintain contact with colleagues within Research Computing and the broader Princeton computing community to effectively grow and develop software engineering capabilities. Strategic Vision for RSE Contribute to the strategic vision for Research Software Engineering (RSE) at Princeton, as well as contribute to national and international efforts to drive the direction of the RSE profession. Qualifications 7-10 years of some combination of the following: Software development (preferably in a research environment) Supporting computational research and software development in an academic setting Leading a software development team in a research environment that had multiple stakeholders 3-5 years of experience managing people, projects, and/or resources. Demonstrably strong programming skills, particularly in the languages common in research software applications. E.g. Python, C/C++, Fortran, R, MATLAB, and/or Julia. Openly value and espouse software engineering and development activities including requirements analysis, design, implementation, testing, deployment, and maintenance. Exceptional written/oral/interpersonal communication skills, both with regard to technical and non-technical audiences. Excellent organizational and project management skills; ability to prioritize and manage multiple complex initiatives and projects serving various research groups with available resources; ability to respond quickly to changing business needs and priorities. Ability to lead a team of highly competent professionals with varying backgrounds, reporting lines, and responsibilities. Must be a strong mentor and developer of people. Proactive approach to seeking information and ideas from peers, supervisors, and project partners. Education: A bachelor's degree is required. A Masters/Ph.D. is strongly preferred. PREFERRED Strong research background in computational science or engineering, computational social science, and/or digital humanities. Knowledge of Machine Learning or large AI models. Research Software Engineering experience. Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. KNOW YOUR RIGHTS PI21b1ee1-
Senior Principal Engineer Site Reliability Dell Technologies customers rely on our products and services to drive progress. So, we take the service we provide extremely seriously. Service Delivery is all about making sure our technical solutions help clients fulfil their priorities, challenges and initiatives. As trusted advisors, we build in-depth knowledge of what each client wants to achieve. Then we make sure the services delivered by Dell Technologies deliver on all our promises. We also work closely with Sales and Global Services colleagues to develop strategic account growth plans, and to identify and pursue sales opportunities. Join us to do the best work of your career and make a profound social impact as a Senior Principal Engineer - Site Reliability Engineering on our Service Delivery Team in Austin, Texas. What you'll achieve The Senior Principal Engineer- Site Reliability Engineering supporting Artificial Intelligence/Machine Learning/High Performance Compute Solutions, Service Delivery will be responsible for providing the primary management, administration, support, and ongoing maintenance of customer Platforms within a 24x7x365 datacenter environment. This is a technical leadership role. The ideal candidate will play a crucial role in managing and supporting complex solutions and platforms for our prestigious Fortune 100 clients. The role will be expected to work in a positive and collaborative fashion with fellow team members, senior engineering/architect staff, vendors, and customers. The Senior Principal Engineer will assist with process maturation, development, technical standards creation, and drive operational excellence through consistent delivery and best practices. You will: Serve as the top technical expert in deploying, upgrading, troubleshooting Artificial Intelligence/Machine Learning/High Performance Compute Solutions platforms Manage and maintain container platform (Kubernetes, OpenShift) infrastructure, including installation, configuration, and upgrades and optimize system performance, capacity, and availability of the environment Act in the capacity of an SRE / DevOps expert Take the first step towards your dream careerEvery Dell Technologies team member brings something unique to the table. Here's what we are looking for with this role:Essential Requirements Hands on experience working in an infrastructure managed services environment, supporting complex engineered solution in production with Artificial Intelligence/Machine Learning/High Performance Compute Systems and Platforms, Converged/ Hyper-Converged infrastructure along with fluency in AI/ML pipelines, Nvidia GPU optimization, InfiniBand networking, Machine Learning operating systems such as cnvrg.io, Compute Orchestration Platform such as runai etc Expert-level knowledge of cluster provisioning and resource schedulers Programming experience with Python, Go, Ruby, Shell Scripts, PowerShell along with hands on experience with ELK, Prometheus, Grafana, Ansible, Git, or similar technologies Expertise in Kubernetes, OpenShift, Docker, Container Networking, and Cloud Native Platform/ Applications Strong Networking Fundamentals along with Converged Infra (CI)/Hyper Converged Infa (HCI) Management Certification along with hands-on experience with Amazon Kubernetes Service (AKS), Amazon EKS, Google Kubernetes Engine (GKE), Rancher Desirable Requirements BE or MS in Computer Science or Computer Engineering or acceptable combination of equivalent industry experience will be considered Certified Kubernetes / OpenShift Admin, NSX T Certification Who we are We believe that each of us has the power to make an impact. That's why we put our team members at the center of everything we do. If you're looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we're looking for you. Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us. Application closing date: 03/22/2024 Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here. Job ID:R241321 Dell's Flexible & Hybrid Work Culture At Dell Technologies, we believe our best work is done when flexibility is offered. We know that freedom and flexibility are crucial to all our employees no matter where you are located and our flexible and hybrid work style allows team members to have the freedom to ideate, be innovative, and drive results their way. To learn more about our work culture, please visit our locations page.
04/29/2024
Full time
Senior Principal Engineer Site Reliability Dell Technologies customers rely on our products and services to drive progress. So, we take the service we provide extremely seriously. Service Delivery is all about making sure our technical solutions help clients fulfil their priorities, challenges and initiatives. As trusted advisors, we build in-depth knowledge of what each client wants to achieve. Then we make sure the services delivered by Dell Technologies deliver on all our promises. We also work closely with Sales and Global Services colleagues to develop strategic account growth plans, and to identify and pursue sales opportunities. Join us to do the best work of your career and make a profound social impact as a Senior Principal Engineer - Site Reliability Engineering on our Service Delivery Team in Austin, Texas. What you'll achieve The Senior Principal Engineer- Site Reliability Engineering supporting Artificial Intelligence/Machine Learning/High Performance Compute Solutions, Service Delivery will be responsible for providing the primary management, administration, support, and ongoing maintenance of customer Platforms within a 24x7x365 datacenter environment. This is a technical leadership role. The ideal candidate will play a crucial role in managing and supporting complex solutions and platforms for our prestigious Fortune 100 clients. The role will be expected to work in a positive and collaborative fashion with fellow team members, senior engineering/architect staff, vendors, and customers. The Senior Principal Engineer will assist with process maturation, development, technical standards creation, and drive operational excellence through consistent delivery and best practices. You will: Serve as the top technical expert in deploying, upgrading, troubleshooting Artificial Intelligence/Machine Learning/High Performance Compute Solutions platforms Manage and maintain container platform (Kubernetes, OpenShift) infrastructure, including installation, configuration, and upgrades and optimize system performance, capacity, and availability of the environment Act in the capacity of an SRE / DevOps expert Take the first step towards your dream careerEvery Dell Technologies team member brings something unique to the table. Here's what we are looking for with this role:Essential Requirements Hands on experience working in an infrastructure managed services environment, supporting complex engineered solution in production with Artificial Intelligence/Machine Learning/High Performance Compute Systems and Platforms, Converged/ Hyper-Converged infrastructure along with fluency in AI/ML pipelines, Nvidia GPU optimization, InfiniBand networking, Machine Learning operating systems such as cnvrg.io, Compute Orchestration Platform such as runai etc Expert-level knowledge of cluster provisioning and resource schedulers Programming experience with Python, Go, Ruby, Shell Scripts, PowerShell along with hands on experience with ELK, Prometheus, Grafana, Ansible, Git, or similar technologies Expertise in Kubernetes, OpenShift, Docker, Container Networking, and Cloud Native Platform/ Applications Strong Networking Fundamentals along with Converged Infra (CI)/Hyper Converged Infa (HCI) Management Certification along with hands-on experience with Amazon Kubernetes Service (AKS), Amazon EKS, Google Kubernetes Engine (GKE), Rancher Desirable Requirements BE or MS in Computer Science or Computer Engineering or acceptable combination of equivalent industry experience will be considered Certified Kubernetes / OpenShift Admin, NSX T Certification Who we are We believe that each of us has the power to make an impact. That's why we put our team members at the center of everything we do. If you're looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we're looking for you. Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us. Application closing date: 03/22/2024 Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here. Job ID:R241321 Dell's Flexible & Hybrid Work Culture At Dell Technologies, we believe our best work is done when flexibility is offered. We know that freedom and flexibility are crucial to all our employees no matter where you are located and our flexible and hybrid work style allows team members to have the freedom to ideate, be innovative, and drive results their way. To learn more about our work culture, please visit our locations page.
Job Description As a Merkle Senior ML Engineer: You will design and develop innovative, cloud-based solutions involving interconnected machine learning (ML) inference and training systems. You will write robust, production-quality code that contributes to the advancement of engineering solutions at Merkle. You will solve intricate engineering problems to enable a team of data scientists to deliver high-quality, production-ready applications. You will automate CI/CD pipelines using modern DevOps tools and frameworks. You will collaborate closely with a diverse team of 10+ data scientists and engineers across various organizational boundaries. You will spearhead the creation of scalable AI innovations in collaboration with foundation and infrastructure partners. You will report to VP, Analytics and this position is remote
04/29/2024
Full time
Job Description As a Merkle Senior ML Engineer: You will design and develop innovative, cloud-based solutions involving interconnected machine learning (ML) inference and training systems. You will write robust, production-quality code that contributes to the advancement of engineering solutions at Merkle. You will solve intricate engineering problems to enable a team of data scientists to deliver high-quality, production-ready applications. You will automate CI/CD pipelines using modern DevOps tools and frameworks. You will collaborate closely with a diverse team of 10+ data scientists and engineers across various organizational boundaries. You will spearhead the creation of scalable AI innovations in collaboration with foundation and infrastructure partners. You will report to VP, Analytics and this position is remote
Position Summary: As the Machine Learning Engineer working in Penske's Advanced Analytics team, you will be in a high impact role. You will be supporting multiple businesses and functions within Penske with their data science initiatives. You will play a key role in maturing the AI/ML Ops at Penske organization. This is a great opportunity for someone who has some machine learning experience or planning to switch to machine learning as a career choice. Responsibilities As part of Penske's Advanced Analytics team you will be responsible for implementation and operationalization of AI/ML models. You will work with other machine learning engineers, data scientists, software engineers and platform engineers to ensure success of the AI/ML implementations at Penske. Major Responsibilities: Support data scientists with AI/ML model development and deployment with an emphasis on auditability, versioning, and data security. Build and implement applications which makes use of AI/ML models Work with data scientists to ensure ML models are performing within the expected ranges of accuracy Lead Self Service AI (SSAI) initiatives by supporting the citizen data scientists across Penske Support AI/ML platforms like Sage Maker, SAS Viya or Dataiku Design data pipelines and engineering infrastructure to support our enterprise machine learning systems Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. Facilitate the development and deployment of proof-of-concept machine learning systems. Develop and deploy scalable tools and services for our clients to handle machine learning training and inference. Take offline models data scientists build and turn them into a real machine learning production system. Experience in technologies, frameworks and architecture like Java or Python, Angular, React, Spring, Spring Boot, XML, JavaScript, JSON, Application Servers, CI/CD is required. Experience using AI/ML platforms such as Sage Maker, SAS Viya or Dataiku to deploy Models is a significant plus but not required. Ability to identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems. Understanding of the full system development lifecycle. Other projects/tasks as assigned. Penske Qualifications: Bachelor's Degree in Computer Science/Computer Engineering or equivalent years of experience. 1-3 years of experience developing software applications and exposure to Machine Learning Experience in technologies, frameworks, architecture, and design patterns. Strong coding skills in languages like Python and software engineering best practices. Experience in designing and building REST APIs and Microservices is required. Experience with Relational Databases, MySQL, In-Memory databases, NoSQL databases and writing SQL queries. Experience with AWS cloud technologies is a significant plus. Understanding of Machine Learning concepts, MLOps and experience using AI/ML platforms such as Dataiku, Sage Maker, or SAS Viya is a plus but not required. As part of Advanced Analytics team you will be responsible for implementation and operationalization of Self-Service AI Models. Experience customizing Conversation AI platforms is a plus. Ability to identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems. Design data pipelines and engineering infrastructure to support our enterprise machine learning systems at scale is a significant plus Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. is a significant plus. Support model development, with an emphasis on auditability, versioning, and data security. Facilitate the development and deployment of proof-of-concept machine learning systems. Develop and deploy scalable tools and services for our clients to handle machine learning training and inference. Take offline models data scientists build and turn them into a real machine learning production system. Ability to work in a team environment and seek guidance on tasks from senior developers and leads. Regular, predictable, full attendance is an essential function of the job. Must be willing and able to contribute to brainstorming sessions in a meaningful way. Willingness to travel as necessary, work the required schedule, work at the specific location required, complete Penske employment application, submit to a background investigation (to include past employment, education, and criminal history) and drug screening are required. Physical Requirements: The physical and mental demands described here are representative of those that must be met by an associate to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The associate will be required to: read; communicate verbally and/or in written form; remember and analyze certain information; and remember and understand certain instructions or guidelines. While performing the duties of this job, the associate may be required to stand, walk, and sit. The associate is frequently required to use hands to touch, handle, and feel, and to reach with hands and arms. The associate must be able to occasionally lift and/or move up to 25lbs/12kg. Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception and the ability to adjust focus. Penske is an Equal Opportunity Employer. Job Category: Information Technology Job Family: Analytics & Intelligence Address: 100 Gundy Drive Primary Location: US-PA-Reading Employer: Penske Truck Leasing Co., L.P. Req ID:
04/29/2024
Full time
Position Summary: As the Machine Learning Engineer working in Penske's Advanced Analytics team, you will be in a high impact role. You will be supporting multiple businesses and functions within Penske with their data science initiatives. You will play a key role in maturing the AI/ML Ops at Penske organization. This is a great opportunity for someone who has some machine learning experience or planning to switch to machine learning as a career choice. Responsibilities As part of Penske's Advanced Analytics team you will be responsible for implementation and operationalization of AI/ML models. You will work with other machine learning engineers, data scientists, software engineers and platform engineers to ensure success of the AI/ML implementations at Penske. Major Responsibilities: Support data scientists with AI/ML model development and deployment with an emphasis on auditability, versioning, and data security. Build and implement applications which makes use of AI/ML models Work with data scientists to ensure ML models are performing within the expected ranges of accuracy Lead Self Service AI (SSAI) initiatives by supporting the citizen data scientists across Penske Support AI/ML platforms like Sage Maker, SAS Viya or Dataiku Design data pipelines and engineering infrastructure to support our enterprise machine learning systems Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. Facilitate the development and deployment of proof-of-concept machine learning systems. Develop and deploy scalable tools and services for our clients to handle machine learning training and inference. Take offline models data scientists build and turn them into a real machine learning production system. Experience in technologies, frameworks and architecture like Java or Python, Angular, React, Spring, Spring Boot, XML, JavaScript, JSON, Application Servers, CI/CD is required. Experience using AI/ML platforms such as Sage Maker, SAS Viya or Dataiku to deploy Models is a significant plus but not required. Ability to identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems. Understanding of the full system development lifecycle. Other projects/tasks as assigned. Penske Qualifications: Bachelor's Degree in Computer Science/Computer Engineering or equivalent years of experience. 1-3 years of experience developing software applications and exposure to Machine Learning Experience in technologies, frameworks, architecture, and design patterns. Strong coding skills in languages like Python and software engineering best practices. Experience in designing and building REST APIs and Microservices is required. Experience with Relational Databases, MySQL, In-Memory databases, NoSQL databases and writing SQL queries. Experience with AWS cloud technologies is a significant plus. Understanding of Machine Learning concepts, MLOps and experience using AI/ML platforms such as Dataiku, Sage Maker, or SAS Viya is a plus but not required. As part of Advanced Analytics team you will be responsible for implementation and operationalization of Self-Service AI Models. Experience customizing Conversation AI platforms is a plus. Ability to identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems. Design data pipelines and engineering infrastructure to support our enterprise machine learning systems at scale is a significant plus Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. is a significant plus. Support model development, with an emphasis on auditability, versioning, and data security. Facilitate the development and deployment of proof-of-concept machine learning systems. Develop and deploy scalable tools and services for our clients to handle machine learning training and inference. Take offline models data scientists build and turn them into a real machine learning production system. Ability to work in a team environment and seek guidance on tasks from senior developers and leads. Regular, predictable, full attendance is an essential function of the job. Must be willing and able to contribute to brainstorming sessions in a meaningful way. Willingness to travel as necessary, work the required schedule, work at the specific location required, complete Penske employment application, submit to a background investigation (to include past employment, education, and criminal history) and drug screening are required. Physical Requirements: The physical and mental demands described here are representative of those that must be met by an associate to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The associate will be required to: read; communicate verbally and/or in written form; remember and analyze certain information; and remember and understand certain instructions or guidelines. While performing the duties of this job, the associate may be required to stand, walk, and sit. The associate is frequently required to use hands to touch, handle, and feel, and to reach with hands and arms. The associate must be able to occasionally lift and/or move up to 25lbs/12kg. Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception and the ability to adjust focus. Penske is an Equal Opportunity Employer. Job Category: Information Technology Job Family: Analytics & Intelligence Address: 100 Gundy Drive Primary Location: US-PA-Reading Employer: Penske Truck Leasing Co., L.P. Req ID:
Senior Principal Engineer Site Reliability Dell Technologies customers rely on our products and services to drive progress. So, we take the service we provide extremely seriously. Service Delivery is all about making sure our technical solutions help clients fulfil their priorities, challenges and initiatives. As trusted advisors, we build in-depth knowledge of what each client wants to achieve. Then we make sure the services delivered by Dell Technologies deliver on all our promises. We also work closely with Sales and Global Services colleagues to develop strategic account growth plans, and to identify and pursue sales opportunities. Join us to do the best work of your career and make a profound social impact as a Senior Principal Engineer - Site Reliability Engineering on our Service Delivery Team in Austin, Texas. What you'll achieve The Senior Principal Engineer- Site Reliability Engineering supporting Artificial Intelligence/Machine Learning/High Performance Compute Solutions, Service Delivery will be responsible for providing the primary management, administration, support, and ongoing maintenance of customer Platforms within a 24x7x365 datacenter environment. This is a technical leadership role. The ideal candidate will play a crucial role in managing and supporting complex solutions and platforms for our prestigious Fortune 100 clients. The role will be expected to work in a positive and collaborative fashion with fellow team members, senior engineering/architect staff, vendors, and customers. The Senior Principal Engineer will assist with process maturation, development, technical standards creation, and drive operational excellence through consistent delivery and best practices. You will: Serve as the top technical expert in deploying, upgrading, troubleshooting Artificial Intelligence/Machine Learning/High Performance Compute Solutions platforms Manage and maintain container platform (Kubernetes, OpenShift) infrastructure, including installation, configuration, and upgrades and optimize system performance, capacity, and availability of the environment Act in the capacity of an SRE / DevOps expert Take the first step towards your dream careerEvery Dell Technologies team member brings something unique to the table. Here's what we are looking for with this role:Essential Requirements Hands on experience working in an infrastructure managed services environment, supporting complex engineered solution in production with Artificial Intelligence/Machine Learning/High Performance Compute Systems and Platforms, Converged/ Hyper-Converged infrastructure along with fluency in AI/ML pipelines, Nvidia GPU optimization, InfiniBand networking, Machine Learning operating systems such as cnvrg.io, Compute Orchestration Platform such as runai etc Expert-level knowledge of cluster provisioning and resource schedulers Programming experience with Python, Go, Ruby, Shell Scripts, PowerShell along with hands on experience with ELK, Prometheus, Grafana, Ansible, Git, or similar technologies Expertise in Kubernetes, OpenShift, Docker, Container Networking, and Cloud Native Platform/ Applications Strong Networking Fundamentals along with Converged Infra (CI)/Hyper Converged Infa (HCI) Management Certification along with hands-on experience with Amazon Kubernetes Service (AKS), Amazon EKS, Google Kubernetes Engine (GKE), Rancher Desirable Requirements BE or MS in Computer Science or Computer Engineering or acceptable combination of equivalent industry experience will be considered Certified Kubernetes / OpenShift Admin, NSX T Certification Who we are We believe that each of us has the power to make an impact. That's why we put our team members at the center of everything we do. If you're looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we're looking for you. Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us. Application closing date: 03/22/2024 Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here. Job ID:R241321 Dell's Flexible & Hybrid Work Culture At Dell Technologies, we believe our best work is done when flexibility is offered. We know that freedom and flexibility are crucial to all our employees no matter where you are located and our flexible and hybrid work style allows team members to have the freedom to ideate, be innovative, and drive results their way. To learn more about our work culture, please visit our locations page.
04/29/2024
Full time
Senior Principal Engineer Site Reliability Dell Technologies customers rely on our products and services to drive progress. So, we take the service we provide extremely seriously. Service Delivery is all about making sure our technical solutions help clients fulfil their priorities, challenges and initiatives. As trusted advisors, we build in-depth knowledge of what each client wants to achieve. Then we make sure the services delivered by Dell Technologies deliver on all our promises. We also work closely with Sales and Global Services colleagues to develop strategic account growth plans, and to identify and pursue sales opportunities. Join us to do the best work of your career and make a profound social impact as a Senior Principal Engineer - Site Reliability Engineering on our Service Delivery Team in Austin, Texas. What you'll achieve The Senior Principal Engineer- Site Reliability Engineering supporting Artificial Intelligence/Machine Learning/High Performance Compute Solutions, Service Delivery will be responsible for providing the primary management, administration, support, and ongoing maintenance of customer Platforms within a 24x7x365 datacenter environment. This is a technical leadership role. The ideal candidate will play a crucial role in managing and supporting complex solutions and platforms for our prestigious Fortune 100 clients. The role will be expected to work in a positive and collaborative fashion with fellow team members, senior engineering/architect staff, vendors, and customers. The Senior Principal Engineer will assist with process maturation, development, technical standards creation, and drive operational excellence through consistent delivery and best practices. You will: Serve as the top technical expert in deploying, upgrading, troubleshooting Artificial Intelligence/Machine Learning/High Performance Compute Solutions platforms Manage and maintain container platform (Kubernetes, OpenShift) infrastructure, including installation, configuration, and upgrades and optimize system performance, capacity, and availability of the environment Act in the capacity of an SRE / DevOps expert Take the first step towards your dream careerEvery Dell Technologies team member brings something unique to the table. Here's what we are looking for with this role:Essential Requirements Hands on experience working in an infrastructure managed services environment, supporting complex engineered solution in production with Artificial Intelligence/Machine Learning/High Performance Compute Systems and Platforms, Converged/ Hyper-Converged infrastructure along with fluency in AI/ML pipelines, Nvidia GPU optimization, InfiniBand networking, Machine Learning operating systems such as cnvrg.io, Compute Orchestration Platform such as runai etc Expert-level knowledge of cluster provisioning and resource schedulers Programming experience with Python, Go, Ruby, Shell Scripts, PowerShell along with hands on experience with ELK, Prometheus, Grafana, Ansible, Git, or similar technologies Expertise in Kubernetes, OpenShift, Docker, Container Networking, and Cloud Native Platform/ Applications Strong Networking Fundamentals along with Converged Infra (CI)/Hyper Converged Infa (HCI) Management Certification along with hands-on experience with Amazon Kubernetes Service (AKS), Amazon EKS, Google Kubernetes Engine (GKE), Rancher Desirable Requirements BE or MS in Computer Science or Computer Engineering or acceptable combination of equivalent industry experience will be considered Certified Kubernetes / OpenShift Admin, NSX T Certification Who we are We believe that each of us has the power to make an impact. That's why we put our team members at the center of everything we do. If you're looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we're looking for you. Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us. Application closing date: 03/22/2024 Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here. Job ID:R241321 Dell's Flexible & Hybrid Work Culture At Dell Technologies, we believe our best work is done when flexibility is offered. We know that freedom and flexibility are crucial to all our employees no matter where you are located and our flexible and hybrid work style allows team members to have the freedom to ideate, be innovative, and drive results their way. To learn more about our work culture, please visit our locations page.
Role:- Partner closely with the Senior Portfolio Manager to develop data engineering and model prediction tools for systematic trading and monitoring Assist in designing, coding, and maintaining tools for the systematic trading infrastructure of the team Perform data analysis and generate live and historical analytical reports Stay current on state-of-the-art technologies and tools including technical libraries, computing environments and academic research Collaborate with the Senior Portfolio Manager and the trading group in a transparent environment, engaging with the whole investment process Requirements:- Strongly skilled/expert in Python with at least 3 years of experience. Master's, or PhD degree in Computer Science, Engineering, Applied Mathematics, Statistics or related STEM field Strong quantitative skills to leverage while building out quantitative tools for research Experience using statistical or machine learning techniques to build a scalable and robust program 2-5 years of experience in finance or technology Previous exposure to a systematic trading environment or equivalent sell-side experience Experience in efficient database management Knowledge of machine learning and statistical techniques and related libraries Participation in mathematical, programming, or trading competitions Please send a PDF resume to
04/29/2024
Full time
Role:- Partner closely with the Senior Portfolio Manager to develop data engineering and model prediction tools for systematic trading and monitoring Assist in designing, coding, and maintaining tools for the systematic trading infrastructure of the team Perform data analysis and generate live and historical analytical reports Stay current on state-of-the-art technologies and tools including technical libraries, computing environments and academic research Collaborate with the Senior Portfolio Manager and the trading group in a transparent environment, engaging with the whole investment process Requirements:- Strongly skilled/expert in Python with at least 3 years of experience. Master's, or PhD degree in Computer Science, Engineering, Applied Mathematics, Statistics or related STEM field Strong quantitative skills to leverage while building out quantitative tools for research Experience using statistical or machine learning techniques to build a scalable and robust program 2-5 years of experience in finance or technology Previous exposure to a systematic trading environment or equivalent sell-side experience Experience in efficient database management Knowledge of machine learning and statistical techniques and related libraries Participation in mathematical, programming, or trading competitions Please send a PDF resume to
Company: US6469 Sysco Payroll, Division of Sysco Resources Services, LLC Zip Code: 77077 Minimum Level of Education: Master's Degree Minimum Years of Experience: 4 Years Employment Type: Full Time Travel Percentage: COMPENSATION INFORMATION: The pay range provided is not indicative of Sysco's actual pay range but is merely algorithmic and provided for generalized comparison. Factors that may be used to determine rate of pay include specific skills, work location, work experience and other individualized factors POSITION SUMMARY: Sysco is seeking a Senior Manager, Data Science to help drive the development of industry-leading predictive models as part of its Enterprise Analytics Team. As a Sr. Manager, you will own the technical development of a portfolio of domain-specific predictive models in support of a functional group (Pricing, Merchandising, Supply Chain & Logistics, etc). There are two primary responsibilities of the Sr. Data Science: Develop predictive analytics ("hands-on-keyboard") via statistical, machine learning, and mathematical models on Sysco's corporate data to get actionable business insights as the technical expert in the portfolio Lead and coach data scientists to succeed in their areas of responsibility and in support of the domain-specific portfolio of models that you are accountable for RESPONSIBILITIES: Lead the technical development of an industry-leading predictive analytics portfolio in support of key functional & business priorities (e.g., demand generation, assortment optimization, supply chain design & optimization) Work with Sr. Directors and Directors throughout Sysco to frame business opportunities and develop appropriate analytic strategies. Ensure the appropriate analytical techniques are used to solve those business opportunities. Implement data science models and visualizations using Python, Tableau and open source libraries Manage, attract, coach, retain, and motivate a world class team of scientists and engineers Lead multiple projects simultaneously and help team resource planning. Perform regular code reviews and give feedback on approach and coding standards to junior data scientists. Design and execute experiments to validate solutions during product rollout and present results to leadership. Collaborate with cross-functional teams to drive business results through various use cases of customer-level in Work with Sysco's technology teams on data integration to architect, build and continuously improve data assets, which are the foundation of data-driven and customer-centric initiatives Research industry leading analytics practices and recommend continuous improvement opportunities for Sysco Represent Sysco in industry events QUALIFICATIONS: Education and / or Experience: Master's degree + 4 years or PhD + 2 years of industry experience in management consulting, strategy, analytics, at a specialized analytics company or in an analytics organization in a corporate setting. Degree should be in mathematics, statistics or computer science or related field; preferred from a top tier University. 4+ years of experience accessing and manipulating data in SQL or NoSQL database environments 3+ years of experience with scientific scripting languages (e.g., Python) and/or object-oriented programming (e.g., C++, Java) 4+ years of experience with Bayesian statistics, regression analysis (beyond linear regression), supervised learning, unsupervised learning or timeseries analysis required Basic Qualifications: Must be able to think conceptually, strategically, and creatively with little oversight or direction (i.e. display thought leadership vs. simply "do" or execute something that was developed or directed by someone else) Must have experience initiating, driving and delivering complex analytical projects Able to perform quantitative analysis using appropriate analytical and visualization tools such as Python, Tableau and open source libraries Strong software design and OOP fundamentals (must be functional in nearly any language) Demonstrated experience using machine learning algorithms in a commercial setting High proficiency in the use of statistical packages, understanding advantages and limitations of each Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms Must be very comfortable with numbers and have a solid understanding of various analytical techniques and where they should be best deployed Must have a basic understanding of the latest trends in database systems and technologies that enable advanced analytics including cloud based solutions such as AWS Preferred Qualifications: Experience in CPG, Retail and /or Foodservice Experience with Agile Software Development Attributes: Inquisitive, innovative, and opportunistic Highly motivated, inspired overachiever Strong communication and interpersonal skills Understanding of end to end process for deploying analytics within a business organization to create value BENEFITS INFORMATION: For information on Sysco's Benefits, please visit OVERVIEW: Sysco is the global leader in foodservice distribution. With over 71,000 colleagues and a fleet of over 13,000 vehicles, Sysco operates approximately 333 distribution facilities worldwide and serves more than 700,000 customer locations. We offer our colleagues the opportunity to grow personally and professionally, to contribute to the success of a dynamic organization, and to serve others in a manner that exceeds their expectations. We're looking for talented, hard-working individuals to join our team. Come grow with us and let us show you why Sysco is at the heart of food and service. AFFIRMATIVE ACTION STATEMENT: Applicants must be currently authorized to work in the United States. We are proud to be an Equal Opportunity and Affirmative Action employer, and consider qualified applicants without regard to race, color, creed, religion, ancestry, national origin, sex, sexual orientation, gender identity, age, disability, veteran status or any other protected factor under federal, state or local law. This opportunity is available through Sysco Corporation, its subsidiaries and affiliates.
04/29/2024
Full time
Company: US6469 Sysco Payroll, Division of Sysco Resources Services, LLC Zip Code: 77077 Minimum Level of Education: Master's Degree Minimum Years of Experience: 4 Years Employment Type: Full Time Travel Percentage: COMPENSATION INFORMATION: The pay range provided is not indicative of Sysco's actual pay range but is merely algorithmic and provided for generalized comparison. Factors that may be used to determine rate of pay include specific skills, work location, work experience and other individualized factors POSITION SUMMARY: Sysco is seeking a Senior Manager, Data Science to help drive the development of industry-leading predictive models as part of its Enterprise Analytics Team. As a Sr. Manager, you will own the technical development of a portfolio of domain-specific predictive models in support of a functional group (Pricing, Merchandising, Supply Chain & Logistics, etc). There are two primary responsibilities of the Sr. Data Science: Develop predictive analytics ("hands-on-keyboard") via statistical, machine learning, and mathematical models on Sysco's corporate data to get actionable business insights as the technical expert in the portfolio Lead and coach data scientists to succeed in their areas of responsibility and in support of the domain-specific portfolio of models that you are accountable for RESPONSIBILITIES: Lead the technical development of an industry-leading predictive analytics portfolio in support of key functional & business priorities (e.g., demand generation, assortment optimization, supply chain design & optimization) Work with Sr. Directors and Directors throughout Sysco to frame business opportunities and develop appropriate analytic strategies. Ensure the appropriate analytical techniques are used to solve those business opportunities. Implement data science models and visualizations using Python, Tableau and open source libraries Manage, attract, coach, retain, and motivate a world class team of scientists and engineers Lead multiple projects simultaneously and help team resource planning. Perform regular code reviews and give feedback on approach and coding standards to junior data scientists. Design and execute experiments to validate solutions during product rollout and present results to leadership. Collaborate with cross-functional teams to drive business results through various use cases of customer-level in Work with Sysco's technology teams on data integration to architect, build and continuously improve data assets, which are the foundation of data-driven and customer-centric initiatives Research industry leading analytics practices and recommend continuous improvement opportunities for Sysco Represent Sysco in industry events QUALIFICATIONS: Education and / or Experience: Master's degree + 4 years or PhD + 2 years of industry experience in management consulting, strategy, analytics, at a specialized analytics company or in an analytics organization in a corporate setting. Degree should be in mathematics, statistics or computer science or related field; preferred from a top tier University. 4+ years of experience accessing and manipulating data in SQL or NoSQL database environments 3+ years of experience with scientific scripting languages (e.g., Python) and/or object-oriented programming (e.g., C++, Java) 4+ years of experience with Bayesian statistics, regression analysis (beyond linear regression), supervised learning, unsupervised learning or timeseries analysis required Basic Qualifications: Must be able to think conceptually, strategically, and creatively with little oversight or direction (i.e. display thought leadership vs. simply "do" or execute something that was developed or directed by someone else) Must have experience initiating, driving and delivering complex analytical projects Able to perform quantitative analysis using appropriate analytical and visualization tools such as Python, Tableau and open source libraries Strong software design and OOP fundamentals (must be functional in nearly any language) Demonstrated experience using machine learning algorithms in a commercial setting High proficiency in the use of statistical packages, understanding advantages and limitations of each Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms Must be very comfortable with numbers and have a solid understanding of various analytical techniques and where they should be best deployed Must have a basic understanding of the latest trends in database systems and technologies that enable advanced analytics including cloud based solutions such as AWS Preferred Qualifications: Experience in CPG, Retail and /or Foodservice Experience with Agile Software Development Attributes: Inquisitive, innovative, and opportunistic Highly motivated, inspired overachiever Strong communication and interpersonal skills Understanding of end to end process for deploying analytics within a business organization to create value BENEFITS INFORMATION: For information on Sysco's Benefits, please visit OVERVIEW: Sysco is the global leader in foodservice distribution. With over 71,000 colleagues and a fleet of over 13,000 vehicles, Sysco operates approximately 333 distribution facilities worldwide and serves more than 700,000 customer locations. We offer our colleagues the opportunity to grow personally and professionally, to contribute to the success of a dynamic organization, and to serve others in a manner that exceeds their expectations. We're looking for talented, hard-working individuals to join our team. Come grow with us and let us show you why Sysco is at the heart of food and service. AFFIRMATIVE ACTION STATEMENT: Applicants must be currently authorized to work in the United States. We are proud to be an Equal Opportunity and Affirmative Action employer, and consider qualified applicants without regard to race, color, creed, religion, ancestry, national origin, sex, sexual orientation, gender identity, age, disability, veteran status or any other protected factor under federal, state or local law. This opportunity is available through Sysco Corporation, its subsidiaries and affiliates.
Company: US6469 Sysco Payroll, Division of Sysco Resources Services, LLC Zip Code: 77077 Minimum Level of Education: Master's Degree Minimum Years of Experience: 4 Years Employment Type: Full Time Travel Percentage: 0 COMPENSATION INFORMATION: The pay range provided is not indicative of Sysco's actual pay range but is merely algorithmic and provided for generalized comparison. Factors that may be used to determine rate of pay include specific skills, work location, work experience and other individualized factors POSITION SUMMARY: Sysco is seeking a Senior Manager, Data Science to help drive the development of industry-leading predictive models as part of its Enterprise Analytics Team. As a Sr. Manager, you will own the technical development of a portfolio of domain-specific predictive models in support of a functional group (Pricing, Merchandising, Supply Chain & Logistics, etc). We work in the office 2 to 3 times a week for in person meetings/problem solving sessions with the team. There are two primary responsibilities of the Sr. Data Science: Develop predictive analytics ("hands-on-keyboard") via statistical, machine learning, and mathematical models on Sysco's corporate data to get actionable business insights as the technical expert in the portfolio Lead and coach data scientists to succeed in their areas of responsibility and in support of the domain-specific portfolio of models that you are accountable for RESPONSIBILITIES: Lead the technical development of an industry-leading predictive analytics portfolio in support of key functional & business priorities (e.g., demand generation, assortment optimization, supply chain design & optimization) Work with Sr. Directors and Directors throughout Sysco to frame business opportunities and develop appropriate analytic strategies. Ensure the appropriate analytical techniques are used to solve those business opportunities. Implement data science models and visualizations using Python, Tableau and open source libraries Manage, attract, coach, retain, and motivate a world class team of scientists and engineers Lead multiple projects simultaneously and help team resource planning. Perform regular code reviews and give feedback on approach and coding standards to junior data scientists. Design and execute experiments to validate solutions during product rollout and present results to leadership. Collaborate with cross-functional teams to drive business results through various use cases of customer-level in Work with Sysco's technology teams on data integration to architect, build and continuously improve data assets, which are the foundation of data-driven and customer-centric initiatives Research industry leading analytics practices and recommend continuous improvement opportunities for Sysco Represent Sysco in industry events QUALIFICATIONS: Education and / or Experience: Master's degree + 4 years or PhD + 2 years of industry experience in management consulting, strategy, analytics, at a specialized analytics company or in an analytics organization in a corporate setting. Degree should be in mathematics, statistics or computer science or related field; preferred from a top tier University. 4+ years of experience accessing and manipulating data in SQL or NoSQL database environments 3+ years of experience with scientific scripting languages (e.g., Python) and/or object-oriented programming (e.g., C++, Java) 4+ years of experience with Bayesian statistics, regression analysis (beyond linear regression), supervised learning, unsupervised learning or timeseries analysis required Basic Qualifications: Must be able to think conceptually, strategically, and creatively with little oversight or direction (i.e. display thought leadership vs. simply "do" or execute something that was developed or directed by someone else) Must have experience initiating, driving and delivering complex analytical projects Able to perform quantitative analysis using appropriate analytical and visualization tools such as Python, Tableau and open source libraries Strong software design and OOP fundamentals (must be functional in nearly any language) Demonstrated experience using machine learning algorithms in a commercial setting High proficiency in the use of statistical packages, understanding advantages and limitations of each Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms Must be very comfortable with numbers and have a solid understanding of various analytical techniques and where they should be best deployed Must have a basic understanding of the latest trends in database systems and technologies that enable advanced analytics including cloud based solutions such as AWS Preferred Qualifications: Experience in CPG, Retail and /or Foodservice Experience with Agile Software Development Attributes: Inquisitive, innovative, and opportunistic Highly motivated, inspired overachiever Strong communication and interpersonal skills Understanding of end to end process for deploying analytics within a business organization to create value BENEFITS INFORMATION: For information on Sysco's Benefits, please visit OVERVIEW: Sysco is the global leader in foodservice distribution. With over 71,000 colleagues and a fleet of over 13,000 vehicles, Sysco operates approximately 333 distribution facilities worldwide and serves more than 700,000 customer locations. We offer our colleagues the opportunity to grow personally and professionally, to contribute to the success of a dynamic organization, and to serve others in a manner that exceeds their expectations. We're looking for talented, hard-working individuals to join our team. Come grow with us and let us show you why Sysco is at the heart of food and service. AFFIRMATIVE ACTION STATEMENT: Applicants must be currently authorized to work in the United States. We are proud to be an Equal Opportunity and Affirmative Action employer, and consider qualified applicants without regard to race, color, creed, religion, ancestry, national origin, sex, sexual orientation, gender identity, age, disability, veteran status or any other protected factor under federal, state or local law. This opportunity is available through Sysco Corporation, its subsidiaries and affiliates.
04/29/2024
Full time
Company: US6469 Sysco Payroll, Division of Sysco Resources Services, LLC Zip Code: 77077 Minimum Level of Education: Master's Degree Minimum Years of Experience: 4 Years Employment Type: Full Time Travel Percentage: 0 COMPENSATION INFORMATION: The pay range provided is not indicative of Sysco's actual pay range but is merely algorithmic and provided for generalized comparison. Factors that may be used to determine rate of pay include specific skills, work location, work experience and other individualized factors POSITION SUMMARY: Sysco is seeking a Senior Manager, Data Science to help drive the development of industry-leading predictive models as part of its Enterprise Analytics Team. As a Sr. Manager, you will own the technical development of a portfolio of domain-specific predictive models in support of a functional group (Pricing, Merchandising, Supply Chain & Logistics, etc). We work in the office 2 to 3 times a week for in person meetings/problem solving sessions with the team. There are two primary responsibilities of the Sr. Data Science: Develop predictive analytics ("hands-on-keyboard") via statistical, machine learning, and mathematical models on Sysco's corporate data to get actionable business insights as the technical expert in the portfolio Lead and coach data scientists to succeed in their areas of responsibility and in support of the domain-specific portfolio of models that you are accountable for RESPONSIBILITIES: Lead the technical development of an industry-leading predictive analytics portfolio in support of key functional & business priorities (e.g., demand generation, assortment optimization, supply chain design & optimization) Work with Sr. Directors and Directors throughout Sysco to frame business opportunities and develop appropriate analytic strategies. Ensure the appropriate analytical techniques are used to solve those business opportunities. Implement data science models and visualizations using Python, Tableau and open source libraries Manage, attract, coach, retain, and motivate a world class team of scientists and engineers Lead multiple projects simultaneously and help team resource planning. Perform regular code reviews and give feedback on approach and coding standards to junior data scientists. Design and execute experiments to validate solutions during product rollout and present results to leadership. Collaborate with cross-functional teams to drive business results through various use cases of customer-level in Work with Sysco's technology teams on data integration to architect, build and continuously improve data assets, which are the foundation of data-driven and customer-centric initiatives Research industry leading analytics practices and recommend continuous improvement opportunities for Sysco Represent Sysco in industry events QUALIFICATIONS: Education and / or Experience: Master's degree + 4 years or PhD + 2 years of industry experience in management consulting, strategy, analytics, at a specialized analytics company or in an analytics organization in a corporate setting. Degree should be in mathematics, statistics or computer science or related field; preferred from a top tier University. 4+ years of experience accessing and manipulating data in SQL or NoSQL database environments 3+ years of experience with scientific scripting languages (e.g., Python) and/or object-oriented programming (e.g., C++, Java) 4+ years of experience with Bayesian statistics, regression analysis (beyond linear regression), supervised learning, unsupervised learning or timeseries analysis required Basic Qualifications: Must be able to think conceptually, strategically, and creatively with little oversight or direction (i.e. display thought leadership vs. simply "do" or execute something that was developed or directed by someone else) Must have experience initiating, driving and delivering complex analytical projects Able to perform quantitative analysis using appropriate analytical and visualization tools such as Python, Tableau and open source libraries Strong software design and OOP fundamentals (must be functional in nearly any language) Demonstrated experience using machine learning algorithms in a commercial setting High proficiency in the use of statistical packages, understanding advantages and limitations of each Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms Must be very comfortable with numbers and have a solid understanding of various analytical techniques and where they should be best deployed Must have a basic understanding of the latest trends in database systems and technologies that enable advanced analytics including cloud based solutions such as AWS Preferred Qualifications: Experience in CPG, Retail and /or Foodservice Experience with Agile Software Development Attributes: Inquisitive, innovative, and opportunistic Highly motivated, inspired overachiever Strong communication and interpersonal skills Understanding of end to end process for deploying analytics within a business organization to create value BENEFITS INFORMATION: For information on Sysco's Benefits, please visit OVERVIEW: Sysco is the global leader in foodservice distribution. With over 71,000 colleagues and a fleet of over 13,000 vehicles, Sysco operates approximately 333 distribution facilities worldwide and serves more than 700,000 customer locations. We offer our colleagues the opportunity to grow personally and professionally, to contribute to the success of a dynamic organization, and to serve others in a manner that exceeds their expectations. We're looking for talented, hard-working individuals to join our team. Come grow with us and let us show you why Sysco is at the heart of food and service. AFFIRMATIVE ACTION STATEMENT: Applicants must be currently authorized to work in the United States. We are proud to be an Equal Opportunity and Affirmative Action employer, and consider qualified applicants without regard to race, color, creed, religion, ancestry, national origin, sex, sexual orientation, gender identity, age, disability, veteran status or any other protected factor under federal, state or local law. This opportunity is available through Sysco Corporation, its subsidiaries and affiliates.
Logic20/20 Inc.
Los Angeles (Downtown), California
Job Description Logic20/20 is seeking a Machine Learning Engineer to lead data science teams that are utilizing artificial intelligence and machine learning to predict and analyze computer vision or customer intent models. This is an exciting opportunity to make an impact by leveraging AI and ML techniques to create production-level systems through the application of machine learning models. What you'll do: Create frameworks to predict a variety of outcomes in different scenarios Create models of customer satisfaction that provide detailed insight into what causes a customer to take different actions Configure a multi-account MLOps environment Collaborate with other data scientists and stakeholders on projects Research and design statistical models to answer target questions, optimize processes and outcomes, and inform decision-making Develop solutions in R or Python Develop production-grade solutions Work in Hadoop, Redshift, and Spark Translate business and product questions into analytics projects Communicate clearly over written and oral channels while translating complex methodologies and analytical results into high-level insights
04/29/2024
Full time
Job Description Logic20/20 is seeking a Machine Learning Engineer to lead data science teams that are utilizing artificial intelligence and machine learning to predict and analyze computer vision or customer intent models. This is an exciting opportunity to make an impact by leveraging AI and ML techniques to create production-level systems through the application of machine learning models. What you'll do: Create frameworks to predict a variety of outcomes in different scenarios Create models of customer satisfaction that provide detailed insight into what causes a customer to take different actions Configure a multi-account MLOps environment Collaborate with other data scientists and stakeholders on projects Research and design statistical models to answer target questions, optimize processes and outcomes, and inform decision-making Develop solutions in R or Python Develop production-grade solutions Work in Hadoop, Redshift, and Spark Translate business and product questions into analytics projects Communicate clearly over written and oral channels while translating complex methodologies and analytical results into high-level insights
Center 3 (19075), United States of America, McLean, Virginia Director, Risk Lead for Generative AI We are growing! The Enterprise Services Business Risk Office provides risk management support to several lines of business including: Tech, Digital, Brand, Enterprise Supplier Management, Capital One Ventures, External Affairs, Capital One Software (COS) and Enterprise AI/ML. We are on the cutting edge of risk management and provide support for new and emerging technologies as well as critical business strategies. Capital One has taken a bold journey to build a technology company, while operating in a complex, highly regulated business. Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of generative AI that few other organizations can. We are committed to building world-class applied science and platform engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance generative AI infrastructure. As an AI/ML risk leader, you will help bring the transformative power of generative AI to reimagine how we serve our customers and businesses who have come to love the products and services we build in a well managed way. As a Director Risk Leader supporting the AI Foundations Program, you will partner with colleagues across AI product, design and tech to deliver results that have a direct impact on customer experience and implement risk solutions to ensure Capital One's continued stability and success. Responsibilities require partnering with a broad set of leaders and stakeholders to identify existing and potential emerging risks in an open, collaborative environment where new ideas and solutions are both welcomed and rewarded. The successful candidate will have knowledge of AI/ML product development processes including an understanding of the model development lifecycle with a lens towards building and scaling AI technologies in a responsible and well managed manner. The candidate will possess an understanding of process management strategies, risk methodologies and have the ability to build relationships with business and risk partners. Core responsibilities include oversight of process hierarchy, critical business process identification and consultation, horizontal support for Enterprise Services controls program, and controls development of internal solutions uniquely designed to meet the challenges of a digital-first, cloud-first business at scale. Leads other associates, when necessary, and ensures best practices executed by the team and shared broadly across the Enterprise. Responsibilities of the Director, Gen AI Risk Guide include and are not limited to: Develop and implement processes to provide independent analysis and effective plans to mitigate risk related to the company's AI/ML management practices. Ensure effective governance by identifying, framing, and presenting risk topics to be discussed by senior management in enterprise risk forums. Advise and consult on the development and management of new Generative AI policies, standards and procedures. Stay current on emerging risk and potential implications to the company as related to accountable domain(s). Collaborate effectively with colleagues, stakeholders, and leaders across multiple organizations to achieve strategic objectives. Coordinate program-related activities and deliverables to ensure effective collaboration within the team and across stakeholder groups. Analyzes data and influences others to proactively identify risks and trends. Balances multiple priorities to help drive business value and support team objectives, while managing tasks and activities related to risk management initiatives Here's what we're looking for in an ideal teammate: You are a critical thinker who seeks to understand the business and its control environment. You possess a relentless focus on quality and timeliness. You adapt to change, embrace bold ideas, and are intellectually curious. You like to ask questions, test assumptions, and challenge conventional thinking. You develop influential relationships based upon shared risk objectives and trust to deliver outstanding business impact. You're a teacher. You do the right thing and lead by example. You have a passion for coaching and investing in the betterment of your team. You lead through change with candor and optimism. You create energy and an environment that fosters trust, collaboration, and belonging, making it easy to attract, hire, and retain top talent. Basic Qualifications: Bachelor's degree or military experience At least 5 years of experience in Process, Project, Risk Management, or Cloud Risk Management At least 3 years direct experience with AI/ML model lifecycle management or operations or deployments Preferred Qualifications: Master's Degree in Computer Science or in an Engineering discipline At least 6 years of experience in Process, Project, Product, Risk Management, or Cloud Risk Management (or equivalent) At least 5 years of hands-on experience with AI/ML specific model lifecycle management including understanding of AI/ML architecture, model risk, data management and Responsible AI practices At least 4 years leading a team Effectively work in white space and bring structure to deliver on our well managed agenda Experience drafting and communicating reports or analytic assessments for executives Ability to communicate clearly and to interact effectively at all levels of the organization, and to influence as warranted and appropriate to drive consensus Experience with identifying and communicating key risks to AI implementations and architectures Experience with risk analysis and reports that describe risk implications to executives Ability to manage multiple high-visibility and high-impact projects while maintaining superior results Familiarity with AI/ML frameworks (NIST AI) Prior experience working in financial services or other highly regulated sectors Experience with security best practices for generative AI development and deployments At this time, Capital One will not sponsor a new applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $233,100 - $266,000 for Director, Cyber Risk & Analysis Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . click apply for full job details
04/28/2024
Full time
Center 3 (19075), United States of America, McLean, Virginia Director, Risk Lead for Generative AI We are growing! The Enterprise Services Business Risk Office provides risk management support to several lines of business including: Tech, Digital, Brand, Enterprise Supplier Management, Capital One Ventures, External Affairs, Capital One Software (COS) and Enterprise AI/ML. We are on the cutting edge of risk management and provide support for new and emerging technologies as well as critical business strategies. Capital One has taken a bold journey to build a technology company, while operating in a complex, highly regulated business. Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of generative AI that few other organizations can. We are committed to building world-class applied science and platform engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance generative AI infrastructure. As an AI/ML risk leader, you will help bring the transformative power of generative AI to reimagine how we serve our customers and businesses who have come to love the products and services we build in a well managed way. As a Director Risk Leader supporting the AI Foundations Program, you will partner with colleagues across AI product, design and tech to deliver results that have a direct impact on customer experience and implement risk solutions to ensure Capital One's continued stability and success. Responsibilities require partnering with a broad set of leaders and stakeholders to identify existing and potential emerging risks in an open, collaborative environment where new ideas and solutions are both welcomed and rewarded. The successful candidate will have knowledge of AI/ML product development processes including an understanding of the model development lifecycle with a lens towards building and scaling AI technologies in a responsible and well managed manner. The candidate will possess an understanding of process management strategies, risk methodologies and have the ability to build relationships with business and risk partners. Core responsibilities include oversight of process hierarchy, critical business process identification and consultation, horizontal support for Enterprise Services controls program, and controls development of internal solutions uniquely designed to meet the challenges of a digital-first, cloud-first business at scale. Leads other associates, when necessary, and ensures best practices executed by the team and shared broadly across the Enterprise. Responsibilities of the Director, Gen AI Risk Guide include and are not limited to: Develop and implement processes to provide independent analysis and effective plans to mitigate risk related to the company's AI/ML management practices. Ensure effective governance by identifying, framing, and presenting risk topics to be discussed by senior management in enterprise risk forums. Advise and consult on the development and management of new Generative AI policies, standards and procedures. Stay current on emerging risk and potential implications to the company as related to accountable domain(s). Collaborate effectively with colleagues, stakeholders, and leaders across multiple organizations to achieve strategic objectives. Coordinate program-related activities and deliverables to ensure effective collaboration within the team and across stakeholder groups. Analyzes data and influences others to proactively identify risks and trends. Balances multiple priorities to help drive business value and support team objectives, while managing tasks and activities related to risk management initiatives Here's what we're looking for in an ideal teammate: You are a critical thinker who seeks to understand the business and its control environment. You possess a relentless focus on quality and timeliness. You adapt to change, embrace bold ideas, and are intellectually curious. You like to ask questions, test assumptions, and challenge conventional thinking. You develop influential relationships based upon shared risk objectives and trust to deliver outstanding business impact. You're a teacher. You do the right thing and lead by example. You have a passion for coaching and investing in the betterment of your team. You lead through change with candor and optimism. You create energy and an environment that fosters trust, collaboration, and belonging, making it easy to attract, hire, and retain top talent. Basic Qualifications: Bachelor's degree or military experience At least 5 years of experience in Process, Project, Risk Management, or Cloud Risk Management At least 3 years direct experience with AI/ML model lifecycle management or operations or deployments Preferred Qualifications: Master's Degree in Computer Science or in an Engineering discipline At least 6 years of experience in Process, Project, Product, Risk Management, or Cloud Risk Management (or equivalent) At least 5 years of hands-on experience with AI/ML specific model lifecycle management including understanding of AI/ML architecture, model risk, data management and Responsible AI practices At least 4 years leading a team Effectively work in white space and bring structure to deliver on our well managed agenda Experience drafting and communicating reports or analytic assessments for executives Ability to communicate clearly and to interact effectively at all levels of the organization, and to influence as warranted and appropriate to drive consensus Experience with identifying and communicating key risks to AI implementations and architectures Experience with risk analysis and reports that describe risk implications to executives Ability to manage multiple high-visibility and high-impact projects while maintaining superior results Familiarity with AI/ML frameworks (NIST AI) Prior experience working in financial services or other highly regulated sectors Experience with security best practices for generative AI development and deployments At this time, Capital One will not sponsor a new applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $233,100 - $266,000 for Director, Cyber Risk & Analysis Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . click apply for full job details
Lead Mechanic Key Duties & Core Responsibilities: Manage equipment repairs and preventive maintenance for fleet of equipment and trucks Coordinate and execute diagnostics/repairs, parts orders and clearly communicate the ramifications to senior management Must be self-driven and able to work independently to accomplish strategic tasks within the organization Maintain, track, update and manage materials, tools, parts and equipment inventory Manage small group of DOT certified drivers to ensure they are following all applicable rules/regulations Certified Diesel Mechanic or equivalent experience. Responsible for organization and safety of shop, yard and buildings Manage Shop and storage area Verify processes are put into place to accurately repair and service equipment, trucks and trailers Create a Clean and Safe Working Shop Environment Make sure all shop tools and diagnostic equipment are kept in good order and updated Perform basic maintenance including rotating tires, checking fluid levels, and changing oil on company owned trucks Repair or replace worn parts and systems such as spark plugs, wheel bearings, brake pads, fuel systems, and sensors Test systems and individual parts to ensure the proper working order and/or to evaluate the degree of damage Determine appropriate repair measures based on research, peer-to-peer examination, and experience Coordinate with Fleet Manger for daily/weekly schedule Minimum of class B drivers license Perform repairs thoroughly and accurately, considering original repair strategy and manufacturer specifications Other duties as assigned Physical Demands Must be able to climb on and off heavy mobile equipment safely This job demands that approximately 80% of your time is standing/moving/lifting and 20% you re your time is sitting performing administrative responsibilities Ability to lift and carry, on a frequent basis, at least 50 pounds and, at times, as much as 90 pounds, as may be assigned. Work Environment Work is performed indoors and outdoors in all weather conditions Work environment periodically exposes the employees to high levels of noise, grease, and dust that is typically associated with a construction project/shop Employee regularly works near heavy equipment and moving machinery Work may involve a variety of substances commonly found on construction sites/shops such as oil, grease, gasoline, diesel fuel Cultural & Behavioral Expectations: • Communicate effectively and work collaboratively with team to develop positive and professional working relationship with clients, developers, city and state inspectors. • Live by and promote a culture of ownership and accountability. Don t cast blame and take responsibility for problems. When problems arise, find solutions first. • Be humble enough to admit when an answer is unknown. Communicate that a solution will be found by consulting the appropriate knowledge expert. • Operate with honesty and transparency. Use judgement on level of transparency. • Give credit to the team, and make successes about the collective (employees, subcontractors, etc.). • Delegate to the team. Allow members to take responsibility. Hold them accountable. • Listen to understand before listening to respond. • Practice a high level of emotional intelligence. Reflect often, encourage After Action Reviews. • Mistakes happen. Use them as learning experiences. • Ask for help during trying times. • Engage in healthy conflict, use this to explore alternative perspectives and implement new ideas. • Use appropriate communication methods. Know your audience and understand appropriateness of email, text, phone call or in-person communication styles. • Foster positive relationships with ALL project stakeholders; including architects, engineers, neighbors, homeowners, subcontractors, and suppliers. A future project lead can come from unsuspected sources. Relationships are a catalyst for opportunity. Benefits: Health insurance, dental insurance, vision insurance, PTO, Profit sharing, and company pickup service truck. Please email your resume with contact information to Email:
04/28/2024
Full time
Lead Mechanic Key Duties & Core Responsibilities: Manage equipment repairs and preventive maintenance for fleet of equipment and trucks Coordinate and execute diagnostics/repairs, parts orders and clearly communicate the ramifications to senior management Must be self-driven and able to work independently to accomplish strategic tasks within the organization Maintain, track, update and manage materials, tools, parts and equipment inventory Manage small group of DOT certified drivers to ensure they are following all applicable rules/regulations Certified Diesel Mechanic or equivalent experience. Responsible for organization and safety of shop, yard and buildings Manage Shop and storage area Verify processes are put into place to accurately repair and service equipment, trucks and trailers Create a Clean and Safe Working Shop Environment Make sure all shop tools and diagnostic equipment are kept in good order and updated Perform basic maintenance including rotating tires, checking fluid levels, and changing oil on company owned trucks Repair or replace worn parts and systems such as spark plugs, wheel bearings, brake pads, fuel systems, and sensors Test systems and individual parts to ensure the proper working order and/or to evaluate the degree of damage Determine appropriate repair measures based on research, peer-to-peer examination, and experience Coordinate with Fleet Manger for daily/weekly schedule Minimum of class B drivers license Perform repairs thoroughly and accurately, considering original repair strategy and manufacturer specifications Other duties as assigned Physical Demands Must be able to climb on and off heavy mobile equipment safely This job demands that approximately 80% of your time is standing/moving/lifting and 20% you re your time is sitting performing administrative responsibilities Ability to lift and carry, on a frequent basis, at least 50 pounds and, at times, as much as 90 pounds, as may be assigned. Work Environment Work is performed indoors and outdoors in all weather conditions Work environment periodically exposes the employees to high levels of noise, grease, and dust that is typically associated with a construction project/shop Employee regularly works near heavy equipment and moving machinery Work may involve a variety of substances commonly found on construction sites/shops such as oil, grease, gasoline, diesel fuel Cultural & Behavioral Expectations: • Communicate effectively and work collaboratively with team to develop positive and professional working relationship with clients, developers, city and state inspectors. • Live by and promote a culture of ownership and accountability. Don t cast blame and take responsibility for problems. When problems arise, find solutions first. • Be humble enough to admit when an answer is unknown. Communicate that a solution will be found by consulting the appropriate knowledge expert. • Operate with honesty and transparency. Use judgement on level of transparency. • Give credit to the team, and make successes about the collective (employees, subcontractors, etc.). • Delegate to the team. Allow members to take responsibility. Hold them accountable. • Listen to understand before listening to respond. • Practice a high level of emotional intelligence. Reflect often, encourage After Action Reviews. • Mistakes happen. Use them as learning experiences. • Ask for help during trying times. • Engage in healthy conflict, use this to explore alternative perspectives and implement new ideas. • Use appropriate communication methods. Know your audience and understand appropriateness of email, text, phone call or in-person communication styles. • Foster positive relationships with ALL project stakeholders; including architects, engineers, neighbors, homeowners, subcontractors, and suppliers. A future project lead can come from unsuspected sources. Relationships are a catalyst for opportunity. Benefits: Health insurance, dental insurance, vision insurance, PTO, Profit sharing, and company pickup service truck. Please email your resume with contact information to Email:
Locations: VA - McLean, United States of America, McLean, Virginia Sr Distinguished Engineer, Generative AI Systems - (Remote- Eligible) Sr Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 9 years of experience designing and building distributed computing HPC and large-scale ML systems At least 6 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $321,500 - $366,900 for Sr Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $340,500 - $388,700 for Sr Distinguished Machine Learning Engineer Remote (Regardless of Location): $272,400 - $310,900 for Sr Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/28/2024
Full time
Locations: VA - McLean, United States of America, McLean, Virginia Sr Distinguished Engineer, Generative AI Systems - (Remote- Eligible) Sr Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 9 years of experience designing and building distributed computing HPC and large-scale ML systems At least 6 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $321,500 - $366,900 for Sr Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $340,500 - $388,700 for Sr Distinguished Machine Learning Engineer Remote (Regardless of Location): $272,400 - $310,900 for Sr Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead Mechanic Key Duties & Core Responsibilities: Manage equipment repairs and preventive maintenance for fleet of equipment and trucks Coordinate and execute diagnostics/repairs, parts orders and clearly communicate the ramifications to senior management Must be self-driven and able to work independently to accomplish strategic tasks within the organization Maintain, track, update and manage materials, tools, parts and equipment inventory Manage small group of DOT certified drivers to ensure they are following all applicable rules/regulations Certified Diesel Mechanic or equivalent experience. Responsible for organization and safety of shop, yard and buildings Manage Shop and storage area Verify processes are put into place to accurately repair and service equipment, trucks and trailers Create a Clean and Safe Working Shop Environment Make sure all shop tools and diagnostic equipment are kept in good order and updated Perform basic maintenance including rotating tires, checking fluid levels, and changing oil on company owned trucks Repair or replace worn parts and systems such as spark plugs, wheel bearings, brake pads, fuel systems, and sensors Test systems and individual parts to ensure the proper working order and/or to evaluate the degree of damage Determine appropriate repair measures based on research, peer-to-peer examination, and experience Coordinate with Fleet Manger for daily/weekly schedule Minimum of class B drivers license Perform repairs thoroughly and accurately, considering original repair strategy and manufacturer specifications Other duties as assigned Physical Demands Must be able to climb on and off heavy mobile equipment safely This job demands that approximately 80% of your time is standing/moving/lifting and 20% you re your time is sitting performing administrative responsibilities Ability to lift and carry, on a frequent basis, at least 50 pounds and, at times, as much as 90 pounds, as may be assigned. Work Environment Work is performed indoors and outdoors in all weather conditions Work environment periodically exposes the employees to high levels of noise, grease, and dust that is typically associated with a construction project/shop Employee regularly works near heavy equipment and moving machinery Work may involve a variety of substances commonly found on construction sites/shops such as oil, grease, gasoline, diesel fuel Cultural & Behavioral Expectations: • Communicate effectively and work collaboratively with team to develop positive and professional working relationship with clients, developers, city and state inspectors. • Live by and promote a culture of ownership and accountability. Don t cast blame and take responsibility for problems. When problems arise, find solutions first. • Be humble enough to admit when an answer is unknown. Communicate that a solution will be found by consulting the appropriate knowledge expert. • Operate with honesty and transparency. Use judgement on level of transparency. • Give credit to the team, and make successes about the collective (employees, subcontractors, etc.). • Delegate to the team. Allow members to take responsibility. Hold them accountable. • Listen to understand before listening to respond. • Practice a high level of emotional intelligence. Reflect often, encourage After Action Reviews. • Mistakes happen. Use them as learning experiences. • Ask for help during trying times. • Engage in healthy conflict, use this to explore alternative perspectives and implement new ideas. • Use appropriate communication methods. Know your audience and understand appropriateness of email, text, phone call or in-person communication styles. • Foster positive relationships with ALL project stakeholders; including architects, engineers, neighbors, homeowners, subcontractors, and suppliers. A future project lead can come from unsuspected sources. Relationships are a catalyst for opportunity. Benefits: Health insurance, dental insurance, vision insurance, PTO, Profit sharing, and company pickup service truck. Please email your resume with contact information to Email:
04/28/2024
Full time
Lead Mechanic Key Duties & Core Responsibilities: Manage equipment repairs and preventive maintenance for fleet of equipment and trucks Coordinate and execute diagnostics/repairs, parts orders and clearly communicate the ramifications to senior management Must be self-driven and able to work independently to accomplish strategic tasks within the organization Maintain, track, update and manage materials, tools, parts and equipment inventory Manage small group of DOT certified drivers to ensure they are following all applicable rules/regulations Certified Diesel Mechanic or equivalent experience. Responsible for organization and safety of shop, yard and buildings Manage Shop and storage area Verify processes are put into place to accurately repair and service equipment, trucks and trailers Create a Clean and Safe Working Shop Environment Make sure all shop tools and diagnostic equipment are kept in good order and updated Perform basic maintenance including rotating tires, checking fluid levels, and changing oil on company owned trucks Repair or replace worn parts and systems such as spark plugs, wheel bearings, brake pads, fuel systems, and sensors Test systems and individual parts to ensure the proper working order and/or to evaluate the degree of damage Determine appropriate repair measures based on research, peer-to-peer examination, and experience Coordinate with Fleet Manger for daily/weekly schedule Minimum of class B drivers license Perform repairs thoroughly and accurately, considering original repair strategy and manufacturer specifications Other duties as assigned Physical Demands Must be able to climb on and off heavy mobile equipment safely This job demands that approximately 80% of your time is standing/moving/lifting and 20% you re your time is sitting performing administrative responsibilities Ability to lift and carry, on a frequent basis, at least 50 pounds and, at times, as much as 90 pounds, as may be assigned. Work Environment Work is performed indoors and outdoors in all weather conditions Work environment periodically exposes the employees to high levels of noise, grease, and dust that is typically associated with a construction project/shop Employee regularly works near heavy equipment and moving machinery Work may involve a variety of substances commonly found on construction sites/shops such as oil, grease, gasoline, diesel fuel Cultural & Behavioral Expectations: • Communicate effectively and work collaboratively with team to develop positive and professional working relationship with clients, developers, city and state inspectors. • Live by and promote a culture of ownership and accountability. Don t cast blame and take responsibility for problems. When problems arise, find solutions first. • Be humble enough to admit when an answer is unknown. Communicate that a solution will be found by consulting the appropriate knowledge expert. • Operate with honesty and transparency. Use judgement on level of transparency. • Give credit to the team, and make successes about the collective (employees, subcontractors, etc.). • Delegate to the team. Allow members to take responsibility. Hold them accountable. • Listen to understand before listening to respond. • Practice a high level of emotional intelligence. Reflect often, encourage After Action Reviews. • Mistakes happen. Use them as learning experiences. • Ask for help during trying times. • Engage in healthy conflict, use this to explore alternative perspectives and implement new ideas. • Use appropriate communication methods. Know your audience and understand appropriateness of email, text, phone call or in-person communication styles. • Foster positive relationships with ALL project stakeholders; including architects, engineers, neighbors, homeowners, subcontractors, and suppliers. A future project lead can come from unsuspected sources. Relationships are a catalyst for opportunity. Benefits: Health insurance, dental insurance, vision insurance, PTO, Profit sharing, and company pickup service truck. Please email your resume with contact information to Email:
201 Third Street (61049), United States of America, San Francisco, California Senior Manager, Generative AI Product Engineering - People Leader - (Remote Eligible) Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities, to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Sr. Manager to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services of our capabilities and enable real-time customer-facing applications powered by these capabilities. Examples of projects you will work on include: Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs. Design APIs for performance, real-time applications, scale, ease of use and governance automation. Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience Enable our users to build new AI capabilities Develop tools and processes to monitor API access patterns and operational health. Design and implement AI safety and guardrails in the API layer working closely with researchers. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field. At least 8 years of experience programming with Python, Go, Scala, or C/C++ At least 5 years of experience designing and building and deploying ML applications. At least 2 years of experience mentoring and leading teams developing AI and Machine Learning solutions At least 4 years of people management experience. Preferred Qualifications: Familiarity with building large-scale AI products or platforms for NLP, speech, computer vision, or recommendation systems serving millions of users. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities Familiarity with deploying large neural network models in demanding production environments. Have experience with API security, observability, cloud access control and privacy best practices. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Mgr, Machine Learning Engineering San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Mgr, Machine Learning Engineering Remote (Regardless of Location): $198,900 - $227,000 for Sr. Mgr, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/28/2024
Full time
201 Third Street (61049), United States of America, San Francisco, California Senior Manager, Generative AI Product Engineering - People Leader - (Remote Eligible) Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities, to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Sr. Manager to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services of our capabilities and enable real-time customer-facing applications powered by these capabilities. Examples of projects you will work on include: Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs. Design APIs for performance, real-time applications, scale, ease of use and governance automation. Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience Enable our users to build new AI capabilities Develop tools and processes to monitor API access patterns and operational health. Design and implement AI safety and guardrails in the API layer working closely with researchers. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field. At least 8 years of experience programming with Python, Go, Scala, or C/C++ At least 5 years of experience designing and building and deploying ML applications. At least 2 years of experience mentoring and leading teams developing AI and Machine Learning solutions At least 4 years of people management experience. Preferred Qualifications: Familiarity with building large-scale AI products or platforms for NLP, speech, computer vision, or recommendation systems serving millions of users. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities Familiarity with deploying large neural network models in demanding production environments. Have experience with API security, observability, cloud access control and privacy best practices. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Mgr, Machine Learning Engineering San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Mgr, Machine Learning Engineering Remote (Regardless of Location): $198,900 - $227,000 for Sr. Mgr, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Locations: Sales - CA - San Francisco, United States of America, San Francisco, California Distinguished Engineer, Generative AI Systems (Remote Eligible) Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/28/2024
Full time
Locations: Sales - CA - San Francisco, United States of America, San Francisco, California Distinguished Engineer, Generative AI Systems (Remote Eligible) Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Locations: Sales - CA - San Francisco, United States of America, San Francisco, California Distinguished Engineer, Generative AI Systems (Remote Eligible) Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/28/2024
Full time
Locations: Sales - CA - San Francisco, United States of America, San Francisco, California Distinguished Engineer, Generative AI Systems (Remote Eligible) Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Job Description About the Role: Payments has become a very active/hot area in the last couple of years, creating a strong demand for innovation. This will be a very exciting area in the next 5 to 10 years. Not only is VISA a leader in the payment industry and has been for a long time, but it is also quickly transitioning into a technology company that is fostering an environment for applying the latest technology to solve exciting problems in this area. For a payment system to work well, the risk techniques, performance, and scalability are critical. These techniques and systems can benefit from big data, data mining, artificial intelligence, machine learning, cloud computing, & many other advance technologies and in VISA, we have all of these. If you want to be in the exciting payment space, learn fast, and make big impacts, Artificial Intelligence Platform team within Payment Security & Identity is an ideal place for you! This position is for a Staff Machine Learning Engineer with solid development experience who will focus on creating new capabilities for AI Platform while maturing our code base and development processes. In this position, you are first a passionate and talented developer that can work in a dynamic environment as a member of Agile Scrum teams. Your strong technical leadership, problem-solving abilities, coding, testing and debugging skills is just a start. You must be dedicated to filling product backlog and delivering production-ready code. You must be willing to go beyond the routine and prepared to do a little bit of everything. You will be an integral part of the development team, sometimes investigating new requirements and design and at times refactoring existing functionality for performance and maintainability, but always working on ways to make us more efficient and provide better solutions to our end customers. The role is for a self-organized individual with knowledge of web application and web service development. The candidate will perform hands-on activities including design, documentation, development and test of new functionality. Candidate must be flexible and willing to switch tasks based on team's needs. This position will be based in Austin, TX and reporting to Senior Director of Visa AI as a Service Team. If this sounds exciting, we want to chat and tell you more about our work culture and environment and see if this will be a good fit for both of us. Essential Functions: Collaborate with project team members (Product Managers, Architects, Analysts, Software Engineers, Project Managers, etc.) to ensure development and implementation of new data driven business solutions. Drive development effort End-to-End for on-time delivery of high quality solutions that conform to requirements, conform to the architectural vision, and comply with all applicable standards. Collaborate with senior technical staff and PM to identify, document, plan contingency, track and manage risks and issues until all are resolved Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a precise and timely manner. This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
04/28/2024
Full time
Job Description About the Role: Payments has become a very active/hot area in the last couple of years, creating a strong demand for innovation. This will be a very exciting area in the next 5 to 10 years. Not only is VISA a leader in the payment industry and has been for a long time, but it is also quickly transitioning into a technology company that is fostering an environment for applying the latest technology to solve exciting problems in this area. For a payment system to work well, the risk techniques, performance, and scalability are critical. These techniques and systems can benefit from big data, data mining, artificial intelligence, machine learning, cloud computing, & many other advance technologies and in VISA, we have all of these. If you want to be in the exciting payment space, learn fast, and make big impacts, Artificial Intelligence Platform team within Payment Security & Identity is an ideal place for you! This position is for a Staff Machine Learning Engineer with solid development experience who will focus on creating new capabilities for AI Platform while maturing our code base and development processes. In this position, you are first a passionate and talented developer that can work in a dynamic environment as a member of Agile Scrum teams. Your strong technical leadership, problem-solving abilities, coding, testing and debugging skills is just a start. You must be dedicated to filling product backlog and delivering production-ready code. You must be willing to go beyond the routine and prepared to do a little bit of everything. You will be an integral part of the development team, sometimes investigating new requirements and design and at times refactoring existing functionality for performance and maintainability, but always working on ways to make us more efficient and provide better solutions to our end customers. The role is for a self-organized individual with knowledge of web application and web service development. The candidate will perform hands-on activities including design, documentation, development and test of new functionality. Candidate must be flexible and willing to switch tasks based on team's needs. This position will be based in Austin, TX and reporting to Senior Director of Visa AI as a Service Team. If this sounds exciting, we want to chat and tell you more about our work culture and environment and see if this will be a good fit for both of us. Essential Functions: Collaborate with project team members (Product Managers, Architects, Analysts, Software Engineers, Project Managers, etc.) to ensure development and implementation of new data driven business solutions. Drive development effort End-to-End for on-time delivery of high quality solutions that conform to requirements, conform to the architectural vision, and comply with all applicable standards. Collaborate with senior technical staff and PM to identify, document, plan contingency, track and manage risks and issues until all are resolved Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a precise and timely manner. This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
Locations: Sales - CA - San Francisco, United States of America, San Francisco, California Distinguished Engineer, Generative AI Systems (Remote Eligible) Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/27/2024
Full time
Locations: Sales - CA - San Francisco, United States of America, San Francisco, California Distinguished Engineer, Generative AI Systems (Remote Eligible) Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
314 Main Street (21020), United States of America, Cambridge, Massachusetts Senior Lead Engineer - Generative AI Product Engineering Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities, to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Sr. Lead Engineer to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services of our capabilities and enable real-time customer-facing applications powered by these capabilities. Examples of projects you will work on include: Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs. Design APIs for performance, real-time applications, scale, ease of use and governance automation. Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience Enable our users to build new AI capabilities Develop tools and processes to monitor API access patterns and operational health. Design and implement AI safety and guardrails in the API layer working closely with researchers. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field. At least 8 years of experience designing and building data-intensive solutions using distributed computing and cache optimization techniques. At least 8 years of experience programming with Python, Go, Scala, or Java At least 1 year of experience building, scaling, and optimizing training or inferencing systems for deep neural networks Preferred Qualifications: Familiarity with building large-scale AI products or platforms for NLP, speech, computer vision, or recommendation systems serving millions of users. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities Familiarity with deploying large neural network models in demanding production environments. Have experience with API security, observability, cloud access control and privacy best practices. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Lead Machine Learning Engineer San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/27/2024
Full time
314 Main Street (21020), United States of America, Cambridge, Massachusetts Senior Lead Engineer - Generative AI Product Engineering Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities, to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Sr. Lead Engineer to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services of our capabilities and enable real-time customer-facing applications powered by these capabilities. Examples of projects you will work on include: Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs. Design APIs for performance, real-time applications, scale, ease of use and governance automation. Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience Enable our users to build new AI capabilities Develop tools and processes to monitor API access patterns and operational health. Design and implement AI safety and guardrails in the API layer working closely with researchers. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field. At least 8 years of experience designing and building data-intensive solutions using distributed computing and cache optimization techniques. At least 8 years of experience programming with Python, Go, Scala, or Java At least 1 year of experience building, scaling, and optimizing training or inferencing systems for deep neural networks Preferred Qualifications: Familiarity with building large-scale AI products or platforms for NLP, speech, computer vision, or recommendation systems serving millions of users. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities Familiarity with deploying large neural network models in demanding production environments. Have experience with API security, observability, cloud access control and privacy best practices. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Lead Machine Learning Engineer San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
130 5th Ave (22130), United States of America, New York, New York Senior Engineer - Generative AI Product Engineering (Remote Eligible) Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Senior Generative AI Engineer to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services that enable real-time customer-facing applications. Examples of projects you will work on include: Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs. Design APIs for performance, real-time applications, scale, ease of use and governance automation. Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience. Enable our users to build new GenAI capabilities. Develop tools and processes to monitor API access patterns and operational health. Design and implement AI safety and guardrails in the API layer working closely with researchers. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 4 years of experience designing and building and deploying ML application platforms. At least 4 years of experience programming with Python, Go, Scala, or Java At least 1 year of experience building, scaling, and optimizing training or inferencing systems for deep neural networks Preferred Qualifications: Familiarity with building large-scale AI products or platforms for NLP, speech, computer vision, or recommendation systems serving millions of users. Familiarity with Graph or Network Theory and Graph ML, including relevant frameworks and libraries such as Deep Graph Learning (DGL) or PyTorch or NetworkX Familiarity with graph querying tools such as Apache Tinkerpop Gremlin, Apache Spark Graphframes, or graph databases. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities. Experience with optimizing ML algorithms and software implementations for speed, efficiency and resource utilization At this time, Capital One will not sponsor a new applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning Engineer San Francisco, California (Hybrid On-Site): $174,900 - $199,700 for Senior Machine Learning Engineer Remote (Regardless of Location): $140,000 - $159,800 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/26/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Senior Engineer - Generative AI Product Engineering (Remote Eligible) Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. We are looking for an experienced Senior Generative AI Engineer to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services that enable real-time customer-facing applications. Examples of projects you will work on include: Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs. Design APIs for performance, real-time applications, scale, ease of use and governance automation. Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience. Enable our users to build new GenAI capabilities. Develop tools and processes to monitor API access patterns and operational health. Design and implement AI safety and guardrails in the API layer working closely with researchers. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 4 years of experience designing and building and deploying ML application platforms. At least 4 years of experience programming with Python, Go, Scala, or Java At least 1 year of experience building, scaling, and optimizing training or inferencing systems for deep neural networks Preferred Qualifications: Familiarity with building large-scale AI products or platforms for NLP, speech, computer vision, or recommendation systems serving millions of users. Familiarity with Graph or Network Theory and Graph ML, including relevant frameworks and libraries such as Deep Graph Learning (DGL) or PyTorch or NetworkX Familiarity with graph querying tools such as Apache Tinkerpop Gremlin, Apache Spark Graphframes, or graph databases. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities. Experience with optimizing ML algorithms and software implementations for speed, efficiency and resource utilization At this time, Capital One will not sponsor a new applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning Engineer San Francisco, California (Hybrid On-Site): $174,900 - $199,700 for Senior Machine Learning Engineer Remote (Regardless of Location): $140,000 - $159,800 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).