Applied ML Scientist

A globally leading technology company is looking for an Applied ML Scientist to design and evaluate next-generation machine learning and GenAI systems that power real-world applications. In this role, you'll develop advanced LLM-based evaluation frameworks, prototype AI-driven solutions, and collaborate closely with cross-functional teams to bring cutting-edge research into production. If you're passionate about building impactful ML systems and driving innovation at scale, we invite you to apply! Job Responsibilities: • Design, develop, and evaluate advanced machine learning models and AI-driven evaluation systems (e.g., LLM-as-a-judge, automated evaluation frameworks) to enhance model performance and reliability. • Prototype, test, and deploy scalable GenAI, LLM, and NLP/NLU solutions for real-world applications, ensuring strong alignment between research insights and production impact. • Collaborate cross-functionally with research, product, and engineering teams to define requirements, identify opportunities for innovation, and translate business needs into technical solutions. • Implement robust software engineering and MLOps practices to ensure reproducible and maintainable ML workflows. Minimum Qualifications: • Strong foundation in machine learning fundamentals with the ability to tackle complex ML challenges. • Experience or proven interest in designing and implementing AI-driven approaches to evaluation (e.g. LLM-as-a-judge, automated evaluation, etc). • Demonstrated ability to develop high-impact language model systems for real-world applications. • Expertise in GenAI, LLM, and/or NLP/NLU evaluation. • Demonstrated ability to identify research directions, rapidly prototype solutions, and drive them to practical impact. • Proficient in software engineering best practices (e.g., modular software design, testing). • Strong proficiency in Python. • Strong proficiency PyTorch, TensorFlow, or Jax. • Excellent communication skills with a proven ability to engage diverse stakeholders. • Experience with MLOps standards, including containerization, orchestration (e.g., Kubernetes), and CI/CD. Preferred Qualifications: Depth in one or more areas is acceptable; candidates are not expected to excel in every listed skill: • Proven experience developing and owning high-impact, developer-facing systems and tools. • Experience developing and evaluating complex agentic systems using LLMs. • Experience adapting and aligning LLMs through various training strategies, e.g. continued pre-training, supervised fine-tuning, and reinforcement learning. • Expertise in uncertainty estimation and calibration, active learning, or related problem spaces. • Experience with ML platform design or ownership • Hands-on experience with large-scale data processing frameworks, e.g. Spark, PySpark, Dask, or Ray. • Track record of contributions to open-source ML projects or publications in top-tier ML conferences (e.g., NeurIPS, ICML, ACL). Type: Contract (W2) Duration: 12 months (with extension possible) Work Location: Seattle, WA (remote) Pay range: $100.00 - $ 120.00/HR