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Senior Data Scientist Machine Learning Operations Gen AI - Remote
Sentara Health Virginia Beach, Virginia
City/State Virginia Beach, VA Work Shift First (Days) Overview: Sentara is hiring for a Senior Data Scientist! This position is fully remote. Overview We are seeking a highly skilled and experienced Data Science ML Operations and Gen AI Engineer (or Senior) to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better healthcare. The Senior Data Scientist will leverage data to improve healthcare outcomes and drive data-driven decision-making. Leveraging expertise in statistical analysis and machine learning, this role will collaborate with cross-functional teams to solve complex healthcare challenges and enhance patient care. This role will directly contribute to advancing medical research, optimizing healthcare processes, and delivering innovative solutions in the healthcare industry. As a Senior ML Engineer on our team, you will play a crucial role in identifying gaps in our existing ML platform and architecting and building solutions to address those gaps. You will also collaborate with the AI team's ML Scientists and our partner data engineering and software development teams to bring ML AND Gen AI models to production and maintain their health and integrity while in production. Your expertise in machine learning and Gen AI, coupled with a strong background in software development, will be instrumental in driving the success of Sentara's AI/ML initiatives. Qualifications: • 5+ years building production software/ML systems, including 1+ years of experience with LLMs/GenAI. • Proficient in Python and one major DL/LLM stack (e.g., PyTorch/Transformers); experience with LangChain/LlamaIndex, vector DBs, and cloud (AWS/Azure/GCP). • Demonstrated delivery of RAG, prompt engineering, evaluation frameworks, and guardrails in production. • Strength in APIs, distributed systems, and ML Ops (K8s, CI/CD, monitoring). • Experience with EPIC health platform is highly preferred • Experience with ML platforms and ML Ops: Demonstrated experience in assessing and improving ML platforms, identifying gaps, and architecting solutions to address them. Strong familiarity with ML platform components such as data ingestion, preprocessing, feature stores, model training, deployment, and monitoring. • Experience with SQL and big data platforms such as Postgres, Redshift and Snowflake • Experience with Agile/Scrum methodology and best practices Preferred: • Previous work experience with Generative AI and ML Ops in healthcare EPIC environment • Understanding of use and implementation of Vector Databases • Kubernetes container orchestration experience Responsibilities • Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions • Lead hands-on delivery of scalable GenAI solutions from problem framing prototyping evaluation production monitoring. • Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation). • Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering. • Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls. • ML platform and ML Ops: Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem. Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement. Develop tools and solutions that help the team build, deploy, and monitor AI/ML solutions efficiently. • System scalability and reliability: Optimize the scalability, performance, and reliability and AI Team solutions by implementing best practices and leveraging industry-standard technologies. Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions. Design scalable and efficient systems that leverage the power of machine learning for enhanced performance and capabilities. • Data processing and workflow pipelines: Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency. Work with data engineering and data platform teams to design and implement robust data pipelines that support the AI team's needs. • Model deployment and monitoring: Evaluate and optimize model prototypes for real-world performance. Work with infrastructure and development teams to integrate ML models into production systems. Work closely with partner teams to communicate and understand technical requirements and challenges. • As part of Sentara's Data Science 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. Specific responsibilities will include: • Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. • Take offline models data scientists build and turn them into a real machine learning production system. Education Bachelor's Degree (Required) Certification/Licensure No specific certification or licensure requirements Experience Required to have 5+ years of experience as a Data Scientist with a strong focus on Azure and Microsoft Data Science, AI, and machine learning toolsets. Required to have strong problem-solving skills and the ability to tackle complex healthcare challenges using data-driven approaches. Can help the Data Science infrastructure building up, working with ML Ops team for model implementation, mentoring and developing junior staff. Required to have s trong proficiency in data analysis, data manipulation, and data visualization using Python. Required to have f amiliarity with healthcare-related datasets, medical terminologies, and electronic health records (EHR) data. Required to have knowledge of statistical techniques, hypothesis testing, and experimental design for healthcare research. Required to have s trong machine learning expertise: Proficient in machine learning algorithms, statistical modeling, and data analysis. Hands-on experience with standard ML frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, XGBoost, TensorFlow, or Keras). Required to have solid understanding of data engineering principles, data structures, and algorithms. Proficient in Python and/or other programming languages commonly used in ML development. Required to have experience in technologies, frameworks and architecture like Java or Python, Angular, React, JSON, Application Servers, CI/CD is preferred. Required to have experience with one or more AI automations platforms like Kubeflow pipeline, MLFlow, Azure Pipeline, AWS Sage Maker Pipeline, Airflow, Jenkins, Spark, Hadoop, Kafka, Jira and GIT. We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for full-time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan •Colleagues have the opportunity to earn an annual discretionary bonus ifestablished system and employee eligibility criteria is met. Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves. In support of our mission "to improve health every day," this is a tobacco-free environment. For positions that are available as remote work, Sentara Health employs associates in the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
04/05/2026
Full time
City/State Virginia Beach, VA Work Shift First (Days) Overview: Sentara is hiring for a Senior Data Scientist! This position is fully remote. Overview We are seeking a highly skilled and experienced Data Science ML Operations and Gen AI Engineer (or Senior) to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better healthcare. The Senior Data Scientist will leverage data to improve healthcare outcomes and drive data-driven decision-making. Leveraging expertise in statistical analysis and machine learning, this role will collaborate with cross-functional teams to solve complex healthcare challenges and enhance patient care. This role will directly contribute to advancing medical research, optimizing healthcare processes, and delivering innovative solutions in the healthcare industry. As a Senior ML Engineer on our team, you will play a crucial role in identifying gaps in our existing ML platform and architecting and building solutions to address those gaps. You will also collaborate with the AI team's ML Scientists and our partner data engineering and software development teams to bring ML AND Gen AI models to production and maintain their health and integrity while in production. Your expertise in machine learning and Gen AI, coupled with a strong background in software development, will be instrumental in driving the success of Sentara's AI/ML initiatives. Qualifications: • 5+ years building production software/ML systems, including 1+ years of experience with LLMs/GenAI. • Proficient in Python and one major DL/LLM stack (e.g., PyTorch/Transformers); experience with LangChain/LlamaIndex, vector DBs, and cloud (AWS/Azure/GCP). • Demonstrated delivery of RAG, prompt engineering, evaluation frameworks, and guardrails in production. • Strength in APIs, distributed systems, and ML Ops (K8s, CI/CD, monitoring). • Experience with EPIC health platform is highly preferred • Experience with ML platforms and ML Ops: Demonstrated experience in assessing and improving ML platforms, identifying gaps, and architecting solutions to address them. Strong familiarity with ML platform components such as data ingestion, preprocessing, feature stores, model training, deployment, and monitoring. • Experience with SQL and big data platforms such as Postgres, Redshift and Snowflake • Experience with Agile/Scrum methodology and best practices Preferred: • Previous work experience with Generative AI and ML Ops in healthcare EPIC environment • Understanding of use and implementation of Vector Databases • Kubernetes container orchestration experience Responsibilities • Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions • Lead hands-on delivery of scalable GenAI solutions from problem framing prototyping evaluation production monitoring. • Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation). • Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering. • Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls. • ML platform and ML Ops: Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem. Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement. Develop tools and solutions that help the team build, deploy, and monitor AI/ML solutions efficiently. • System scalability and reliability: Optimize the scalability, performance, and reliability and AI Team solutions by implementing best practices and leveraging industry-standard technologies. Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions. Design scalable and efficient systems that leverage the power of machine learning for enhanced performance and capabilities. • Data processing and workflow pipelines: Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency. Work with data engineering and data platform teams to design and implement robust data pipelines that support the AI team's needs. • Model deployment and monitoring: Evaluate and optimize model prototypes for real-world performance. Work with infrastructure and development teams to integrate ML models into production systems. Work closely with partner teams to communicate and understand technical requirements and challenges. • As part of Sentara's Data Science 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. Specific responsibilities will include: • Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. • Take offline models data scientists build and turn them into a real machine learning production system. Education Bachelor's Degree (Required) Certification/Licensure No specific certification or licensure requirements Experience Required to have 5+ years of experience as a Data Scientist with a strong focus on Azure and Microsoft Data Science, AI, and machine learning toolsets. Required to have strong problem-solving skills and the ability to tackle complex healthcare challenges using data-driven approaches. Can help the Data Science infrastructure building up, working with ML Ops team for model implementation, mentoring and developing junior staff. Required to have s trong proficiency in data analysis, data manipulation, and data visualization using Python. Required to have f amiliarity with healthcare-related datasets, medical terminologies, and electronic health records (EHR) data. Required to have knowledge of statistical techniques, hypothesis testing, and experimental design for healthcare research. Required to have s trong machine learning expertise: Proficient in machine learning algorithms, statistical modeling, and data analysis. Hands-on experience with standard ML frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, XGBoost, TensorFlow, or Keras). Required to have solid understanding of data engineering principles, data structures, and algorithms. Proficient in Python and/or other programming languages commonly used in ML development. Required to have experience in technologies, frameworks and architecture like Java or Python, Angular, React, JSON, Application Servers, CI/CD is preferred. Required to have experience with one or more AI automations platforms like Kubeflow pipeline, MLFlow, Azure Pipeline, AWS Sage Maker Pipeline, Airflow, Jenkins, Spark, Hadoop, Kafka, Jira and GIT. We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for full-time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan •Colleagues have the opportunity to earn an annual discretionary bonus ifestablished system and employee eligibility criteria is met. Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves. In support of our mission "to improve health every day," this is a tobacco-free environment. For positions that are available as remote work, Sentara Health employs associates in the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
Senior Machine Learning Scientist (USA Remote)
Turnitin Chicago, Illinois
Overview Machine Learning is integral to the continued success of our company. Our product roadmap is exciting and ambitious. You will join a global team of curious, helpful, and independent scientists and engineers, united by a commitment to deliver cutting-edge, well-engineered Machine Learning systems. You will work closely with product and engineering teams across Turnitin to integrate Machine Learning into a broad suite of learning, teaching and integrity products. We are in a unique position to deliver Machine Learning used by hundreds of thousands of instructors teaching millions of students around the world. Your contributions will have global reach and scale. Billions of papers have been submitted to the Turnitin platform, and hundreds of millions of answers have been graded on the Gradescope and Examsoft platforms. Machine Learning powers our AI Writing detection system, gives automated feedback on student writing, investigates authorship of student writing, revolutionizes the creation and grading of assessments, and plays a critical role in many back-end processes. Responsibilities and Requirements Responsibilities and Requirements: We expect Senior Machine Learning Scientists to be versatile and have a well-balanced set of skills. You will focus on model training and maintenance with significant capacity for research (developing novel model architectures), dataset construction, and model hardening (preparing the model and code for production pipelines). Day-to-day, your responsibilities are to: Work with subject matter experts and product owners to determine what questions should be asked and what questions can be answered. Work with subject matter experts to curate, generate, and annotate data, and create optimal datasets following responsible data collection and model maintenance practices. Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary. Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters. Utilize, adopt, and fine-tune Language Models, including third-party LLMs (through prompt engineering and orchestration) and locally hosted LMs. Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings. Optimize models for scaled production usage. Communicate insights, as well as the behavior and limitations of models, to peers, subject matter experts, and product owners. Write clean, efficient, and modular code, with automated tests and appropriate documentation. Stay up to date with technology, make good technological choices, and be able to explain them to the organization. Qualifications Required Qualifications: Experience working with text data to build Deep Learning and ML models, both supervised and unsupervised. Experience with deep learning in other modalities such as vision and speech would be a strong bonus. A strong understanding of the math and theory behind machine learning and deep learning. Software engineering background with at least 8 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review). Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families. Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. A Computer Science background is required as opposed to statistics or pure mathematics. We're an applied science group leaning towards deep learning and therefore software development proficiency is a prerequisite. Excellent communication and teamwork skills. Fluent in written and spoken English. Would be a plus: Familiarity in coding for at-scale production, ranging from best practices to building back-end API services or stand-alone libraries. Essential dev-ops skills (we use Docker, AWS EC2/Batch/Lambda). Familiarity in building front-ends (LLMs or more standard React, Javascript, Flask) for simple demos, POCs and prototypes. Experience with advanced prompting, fine-tuning or training an LLM, open-source or cloud, using industry accepted platforms (such as mosaic.ai or stochastic.ai). Showcase previous work (e.g. via a website, presentation, open source code). Additional Information The expected annual base salary range for this position is: $111,000/year to $185,000/year. This position is bonus eligible / commission-based. As a Remote-First company, actual compensation will be provided in writing at the time of offer, if extended, and is determined by work location and a range of other relevant factors, including but not limited to: experience, skills, degrees, licensures, certifications, and other job-related factors. Internal equity, market and organizational factors are also considered. Total Turnitin maintains a Total Rewards package that is competitive within the local job market. People tend to think about their Total Rewards monetarily - solely as regular pay plus bonus or commission. This is what they earn in exchange for what they do. However, Turnitin delivers more than just these components. Beyond the intrinsic rewards of unleashing your potential to positively impact global education, and thriving in an organization that is free of politics and full of humble, inclusive and collaborative teammates, the extrinsic rewards at Turnitin include generous time off and health and wellness programs that offer choice and flexibility and provide a safety net for the challenges that life presents from time to time. Experience a remote-centric culture that empowers you to work with purpose and accountability in a way that best suits you, supported by a comprehensive package that prioritizes your overall well-being. Our Mission is to ensure the integrity of global education and meaningfully improve learning outcomes. Our Values underpin everything we do. Customer Centric - We realize our mission to ensure integrity and improve learning outcomes by putting educators and learners at the center of everything we do. Passion for Learning - We seek out teammates that are constantly learning and growing and build a workplace which enables them to do so. Integrity - We believe integrity is the heartbeat of Turnitin. It shapes our products, the way we treat each other, and how we work with our customers and vendors. Action & Ownership - We have a bias toward action and empower teammates to make decisions. One Team - We strive to break down silos, collaborate effectively, and celebrate each other's successes. Global Mindset - We respect local cultures and embrace diversity. We think globally and act locally to maximize our impact on education. Global Benefits Remote First Culture Health Care Coverage Education Reimbursement Competitive Paid Time Off 4 Self-Care Days per year National Holidays 2 Founder Days + Juneteenth Observed Paid Volunteer Time Charitable contribution match Monthly Wellness or Home Office Reimbursement Access to Modern Health (mental health platform) Parental Leave Retirement Plan with match/contribution varies by country Seeing Beyond the Job Ad At Turnitin, we recognize it's unrealistic for candidates to fulfill 100% of the criteria in a job ad. We encourage you to apply if you meet the majority of the requirements because we know that skills evolve over time. If you're willing to learn and evolve alongside us, join our team! Turnitin, LLC is committed to the policy that all persons have equal access to its programs, facilities and employment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
04/04/2026
Full time
Overview Machine Learning is integral to the continued success of our company. Our product roadmap is exciting and ambitious. You will join a global team of curious, helpful, and independent scientists and engineers, united by a commitment to deliver cutting-edge, well-engineered Machine Learning systems. You will work closely with product and engineering teams across Turnitin to integrate Machine Learning into a broad suite of learning, teaching and integrity products. We are in a unique position to deliver Machine Learning used by hundreds of thousands of instructors teaching millions of students around the world. Your contributions will have global reach and scale. Billions of papers have been submitted to the Turnitin platform, and hundreds of millions of answers have been graded on the Gradescope and Examsoft platforms. Machine Learning powers our AI Writing detection system, gives automated feedback on student writing, investigates authorship of student writing, revolutionizes the creation and grading of assessments, and plays a critical role in many back-end processes. Responsibilities and Requirements Responsibilities and Requirements: We expect Senior Machine Learning Scientists to be versatile and have a well-balanced set of skills. You will focus on model training and maintenance with significant capacity for research (developing novel model architectures), dataset construction, and model hardening (preparing the model and code for production pipelines). Day-to-day, your responsibilities are to: Work with subject matter experts and product owners to determine what questions should be asked and what questions can be answered. Work with subject matter experts to curate, generate, and annotate data, and create optimal datasets following responsible data collection and model maintenance practices. Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary. Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters. Utilize, adopt, and fine-tune Language Models, including third-party LLMs (through prompt engineering and orchestration) and locally hosted LMs. Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings. Optimize models for scaled production usage. Communicate insights, as well as the behavior and limitations of models, to peers, subject matter experts, and product owners. Write clean, efficient, and modular code, with automated tests and appropriate documentation. Stay up to date with technology, make good technological choices, and be able to explain them to the organization. Qualifications Required Qualifications: Experience working with text data to build Deep Learning and ML models, both supervised and unsupervised. Experience with deep learning in other modalities such as vision and speech would be a strong bonus. A strong understanding of the math and theory behind machine learning and deep learning. Software engineering background with at least 8 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review). Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families. Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. A Computer Science background is required as opposed to statistics or pure mathematics. We're an applied science group leaning towards deep learning and therefore software development proficiency is a prerequisite. Excellent communication and teamwork skills. Fluent in written and spoken English. Would be a plus: Familiarity in coding for at-scale production, ranging from best practices to building back-end API services or stand-alone libraries. Essential dev-ops skills (we use Docker, AWS EC2/Batch/Lambda). Familiarity in building front-ends (LLMs or more standard React, Javascript, Flask) for simple demos, POCs and prototypes. Experience with advanced prompting, fine-tuning or training an LLM, open-source or cloud, using industry accepted platforms (such as mosaic.ai or stochastic.ai). Showcase previous work (e.g. via a website, presentation, open source code). Additional Information The expected annual base salary range for this position is: $111,000/year to $185,000/year. This position is bonus eligible / commission-based. As a Remote-First company, actual compensation will be provided in writing at the time of offer, if extended, and is determined by work location and a range of other relevant factors, including but not limited to: experience, skills, degrees, licensures, certifications, and other job-related factors. Internal equity, market and organizational factors are also considered. Total Turnitin maintains a Total Rewards package that is competitive within the local job market. People tend to think about their Total Rewards monetarily - solely as regular pay plus bonus or commission. This is what they earn in exchange for what they do. However, Turnitin delivers more than just these components. Beyond the intrinsic rewards of unleashing your potential to positively impact global education, and thriving in an organization that is free of politics and full of humble, inclusive and collaborative teammates, the extrinsic rewards at Turnitin include generous time off and health and wellness programs that offer choice and flexibility and provide a safety net for the challenges that life presents from time to time. Experience a remote-centric culture that empowers you to work with purpose and accountability in a way that best suits you, supported by a comprehensive package that prioritizes your overall well-being. Our Mission is to ensure the integrity of global education and meaningfully improve learning outcomes. Our Values underpin everything we do. Customer Centric - We realize our mission to ensure integrity and improve learning outcomes by putting educators and learners at the center of everything we do. Passion for Learning - We seek out teammates that are constantly learning and growing and build a workplace which enables them to do so. Integrity - We believe integrity is the heartbeat of Turnitin. It shapes our products, the way we treat each other, and how we work with our customers and vendors. Action & Ownership - We have a bias toward action and empower teammates to make decisions. One Team - We strive to break down silos, collaborate effectively, and celebrate each other's successes. Global Mindset - We respect local cultures and embrace diversity. We think globally and act locally to maximize our impact on education. Global Benefits Remote First Culture Health Care Coverage Education Reimbursement Competitive Paid Time Off 4 Self-Care Days per year National Holidays 2 Founder Days + Juneteenth Observed Paid Volunteer Time Charitable contribution match Monthly Wellness or Home Office Reimbursement Access to Modern Health (mental health platform) Parental Leave Retirement Plan with match/contribution varies by country Seeing Beyond the Job Ad At Turnitin, we recognize it's unrealistic for candidates to fulfill 100% of the criteria in a job ad. We encourage you to apply if you meet the majority of the requirements because we know that skills evolve over time. If you're willing to learn and evolve alongside us, join our team! Turnitin, LLC is committed to the policy that all persons have equal access to its programs, facilities and employment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

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