Senior Director of Machine Learning

Lead and grow ML engineers, applied scientists, and ML production engineers building AI services end to end — from problem framing through production operation Own the strategy for how we build on top of frontier LLMs: prompt and context design, retrieval, tool and function calling, agentic workflows, structured output reliability, fallback and degradation behavior, latency and cost management Drive the design of the harnesses and glue around LLM calls — orchestration, validation, guardrails, deterministic scaffolding — so probabilistic components produce dependable, auditable outputs inside product and clinical workflows Direct development of in-house deep learning and classical ML models where a custom model outperforms a general-purpose one, including clinical and recommendation use cases such as medication and treatment-plan recommendations surfaced to providers Set the bar for how AI services are productionized: SLOs for accuracy, latency and cost, graceful failure, rollout strategy, and clear ownership of production behavior Make build-versus-fine-tune-versus-prompt decisions deliberately, and revisit them as model capabilities and pricing shift Partner with Clinical and Medical Affairs to ensure clinically-facing models are developed with appropriate oversight, validation, and human-in-the-loop design; ensure providers stay in control of clinical decisions Partner closely with the ML infrastructure and evaluation team members to define evaluation criteria, feedback loops, and annotation needs for every service your team ships — and to hold your team accountable to the resulting metrics Work with Product, Data Science, Engineering, Security, Legal, and Compliance to translate ambiguous business and clinical problems into scoped, high-leverage ML work Establish engineering and scientific standards across the team: experiment design, model documentation, reproducibility, code quality, and responsible AI practices Build the team’s hiring, leveling, and mentorship practices; develop senior individual contributors and managers Act as a senior technical voice in the AI organization, shaping multi-year roadmap and investment decisions and representing AI strategy to executive leadership