Source description
About the role
Bachelor’s degree in Computer Science, Software Engineering, Math, or other related technical degree
5+ years of hands on engineering experience with 2+ years building and deploying machine learning systems including generative AI (LLMS), and a clear track record of impact.
Strong software engineering fundamentals and the ability to ship reliable, well-tested code in Python (or a comparable language) in a production environment.
Practical understanding of modern LLM techniques: prompting, retrieval-augmented generation, fine-tuning, evaluation, and the trade-offs between them.
Comfortability working with messy, real-world data and designing evaluations to know whether a system is actually working.
Strong written and verbal communication; ability to cross-collaborate with clinicians, product managers, and engineers across disciplines.
A bias toward action and ownership: you can take an ambiguous problem, drive it to a result, and bring others along.
Care for the mission. You want your work to translate into better health outcomes for real patients.
Nice to have
Experience applying ML or LLMs in healthcare, life sciences, or another regulated, high-stakes domain.
Experience with clinical NLP, medical knowledge representation, or working with electronic health record data.
Experience building agentic systems, tool-using LLMs, in production.
Experience scaling ML infrastructure — training pipelines, distributed inference, evaluation platforms — for a small, fast-moving team.
Track record of technical leadership: setting direction across teams, mentoring engineers, or publishing influential work.
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