Staff Machine Learning Engineer, EvolutionIQ

• A seasoned ML expert who thrives on first principles problems that no one has ever worked on before
• You love innovation and making an immediate impact – and are constantly driving toward launch and delivery thanks to your high degree of ownership and control
• You love working on new and challenging problems – not incremental or marginal improvements – and you're supercharged by having interesting, unsolved problems continually present themselves
• You are an ML Engineer / Data Scientist with 5+ years of experience, especially in highly scalable production environments, with a proven track record of quickly getting from idea to production
• You have deep exposure to data science & AI tech stacks (sklearn, Keras / PyTorch, LLM / gen AI frameworks, tuning frameworks, A/B experimentation), data analysis & modeling, feel at home in Python/Pandas/Jupyter yet switch seamlessly to work in production environments & pipelines, and strive for scalable technical concepts and solutions
• You’re a team player who is solutions-oriented
• You have crisp written and verbal communication skills and can effectively correspond between technical and non-technical audiences
• You have 2+ years of experience leading teams of 5+ ML engineers in high stakes production environments
• You owned, deployed, and maintained model-serving pipelines in production
• Expert skills at writing clean, efficient, and easy-to-understand code with unit tests and following SWE best practices
• Translate cutting-edge research into production-grade solutions. Turn the latest advancements in AI into scalable, high-impact systems that operate seamlessly in live customer environments
• Experience translating state-of-the-art research papers into production code
• Accustomed to collaborating with data labelers and SMEs
• Experience building production agentic systems

Desirable

• Perform in-depth exploratory data analysis to scope ML opportunities, identify potential issues in the data, and lay the groundwork for model design, training & evaluation strategies
• Suggest and implement new features to improve model performance and business logic
• Work closely with product & engineering stakeholders to identify business opportunities and technical feasibility using ML/AI
• Mentor and guide more junior MLEs across the organization to drive towards technical excellence in ML workflows and product deliveries
• Build ML models for production use, write and review production-quality PRs daily
• Translate client business problems into ML problems
• Build scalable machine learning models for claim time series forecasting,NLP text understanding, and generative AI solutions
• Continue to grow and learn in the data & ML space with a focus on business problems that require making sense of large-scale structured and unstructured datasets