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Hims & Hers, a public healthtech company (NYSE: HIMS), is seeking a Senior Director of Machine Learning to lead the applied AI organization. This is a builder's leadership role owning the strategy and execution of LLM-powered services and custom deep learning models that form the core of the Hims & Hers platform—handling clinical intake, provider support, personalization, and operational workflows.
You will lead and grow a team of ML engineers, applied scientists, and ML production engineers, setting technical direction for how the company builds on top of frontier LLMs and custom models. Key responsibilities include:
- Leading end-to-end AI service development from problem framing through production operation
- Owning strategy for LLM application: prompt and context design, retrieval, tool calling, agentic workflows, structured output reliability, latency and cost management
- Designing orchestration, validation, guardrails, and deterministic scaffolding to make probabilistic components produce dependable, auditable outputs in clinical workflows
- Directing development of in-house deep learning and classical ML models for clinical and recommendation use cases (e.g., medication and treatment-plan recommendations)
- Setting productionization standards: SLOs for accuracy, latency, cost, graceful failure, rollout strategy, and clear ownership
- Making deliberate build-versus-fine-tune-versus-prompt decisions and revisiting them as capabilities and pricing shift
- Partnering with Clinical and Medical Affairs to ensure clinically-facing models have appropriate oversight, validation, and human-in-the-loop design
- Collaborating with ML infrastructure and evaluation teams to define evaluation criteria, feedback loops, and annotation needs
- Working cross-functionally with Product, Data Science, Engineering, Security, Legal, and Compliance to translate business and clinical problems into scoped ML work
- Establishing engineering and scientific standards: experiment design, model documentation, reproducibility, code quality, and responsible AI practices
- Building hiring, leveling, and mentorship practices; developing senior ICs and managers
- Acting as a senior technical voice in the AI organization, shaping multi-year roadmap and representing AI strategy to executive leadership
REQUIREMENTS:
- 14+ years of experience in machine learning and software engineering, including 8+ years leading ML teams and experience managing managers or senior tech leads
- Track record of shipping ML-powered products to production at scale (not prototypes or research) 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, and practical limits of each
- 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: reasoning about service boundaries, data flow, failure modes, and cost alongside model architecture
- Experience balancing model quality against latency, cost, and operational complexity, and making those tradeoffs legible to non-technical partners
- Comfort operating with ambiguity: taking vague, high-value problems and turning them into shipped systems with measurable impact
- Excellent communication skills with ability to influence peers, executives, and clinical stakeholders
- Bonus: experience in healthcare, digital health, or regulated domains; experience with safety-critical ML systems
- Bonus: experience with clinical decision support, clinical NLP, or ML systems where a human expert is the end user
