Senior ML Engineer

Every hire must demonstrate at least Level 1. The expected level will vary depending on the seniority of the role.

What you’ll be doing

• Own ML projects end-to-end: take problems from exploration through production deployment and keep iterating once real users are on them;
• Build agentic LLM systems: design multi-step workflows with tool use, retrieval, and orchestration, and make them reliable enough for clinical settings;
• Treat evaluation as core engineering work: build eval sets, offline and online harnesses, LLM-as-judge pipelines with human review, and regression tests that catch quality drops before they reach users;