Sr. Director of Machine Learning

Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We're looking for a Sr. Director of Machine Learning to lead the teams building the AI services at the core of the Hims & Hers experience. This leader owns the applied side of the AI portfolio: LLM-powered services for clinical intake, provider support, personalization, and operational workflows, as well as in-house deep learning models that drive recommendations and predictions. This is a builder's leadership role focused on turning foundation models and custom models into dependable production services. Hims & Hers is a public company traded on the NYSE under the ticker HIMS.

Responsibilities

Lead and grow ML engineers, applied scientists, and ML production engineers building AI services end to end; Own the strategy for building 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 harnesses and glue around LLM calls (orchestration, validation, guardrails, deterministic scaffolding); Direct development of in-house deep learning and classical ML models, including clinical and recommendation use cases; Set the bar for productionizing AI services (SLOs for accuracy, latency and cost, graceful failure, rollout strategy, production ownership); Make build-versus-fine-tune-versus-prompt decisions and revisit them as model capabilities and pricing shift; Partner with Clinical and Medical Affairs to ensure appropriate oversight, validation, and human-in-the-loop design for clinically-facing models; Partner with ML infrastructure and evaluation team members to define evaluation criteria, feedback loops, and annotation needs; Work with Product, Data Science, Engineering, Security, Legal, and Compliance to translate ambiguous business and clinical problems into scoped ML work; Establish engineering and scientific standards (experiment design, model documentation, reproducibility, code quality, 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

Requirements

14+ years of experience in machine learning and software engineering; 8+ years leading ML teams and experience managing managers or senior tech leads; Track record of shipping ML-powered products to production at scale and owning them operationally over time; Depth in modern LLM application development (RAG, prompt engineering, fine-tuning and adaptation, evaluation, agent and tool-calling architectures); Real experience training and deploying deep learning models (recommendation, ranking, classification, or sequence models) where model quality directly affects user or business outcomes; Strong software architecture judgment (service boundaries, data flow, failure modes, cost); Experience balancing model quality against latency, cost, and operational complexity; Comfort operating with ambiguity; Excellent communication skills, with the ability to influence peers, executives, and clinical stakeholders

Nice to have

Experience in healthcare, digital health, or another regulated domain or with safety-critical ML systems; Experience with clinical decision support, clinical NLP, or ML systems where a human expert is the end user