Senior ML Engineer

Role overview Own the experiments and production improvements behind machine learning systems that assess whether products meet eligibility rules for tax-advantaged health spending. The work spans model design, evaluation, and expanding classification to new product categories, with decisions grounded in labeled data and close coordination with clinical and legal specialists.

Responsibilities - Develop and compare classifiers using approaches such as prompting, retrieval, fine-tuning, and combinations of models. - Form hypotheses, establish baselines, run experiments, analyze errors, and move successful changes into production. - Build evaluation datasets and metrics, including processes for defining and labeling correct outcomes. - Assess new models and research for potential improvements to accuracy or operating cost. - Expand classification coverage and prototype other useful applications for available models and data. - Work with clinical operations and legal partners to turn eligibility standards into testable system behavior; document findings and share practical AI knowledge with engineers.

Requirements - At least five years in engineering or applied research, including two or more years working hands-on with machine learning models on real problems. - Strong experimental practice, including clear hypotheses, sound baselines, ablations, and defensible conclusions. - Experience designing ways to evaluate AI systems and define and measure correctness. - Practical experience with foundation-model techniques such as prompting, fine-tuning, retrieval, or agent design. - Strong Python skills and the engineering ability to take experiments through to production. - Evidence of independently taking an ambiguous ML problem from an initial experiment to a production system. - A public example of experimental work, such as a paper, open-source project, or technical write-up.

Nice to have - Experience with healthcare or regulatory classification, or with coordinating multiple models.

Benefits and work setup - Remote work, health, dental, and vision coverage, employer HSA contributions, and a 401(k). - Unlimited paid time off, coworking and learning stipends, and recurring company and team gatherings. - The source lists a base pay range of $205,000–$250,000 plus stock options.