Sr. Director of Machine Learning (AI)

Location: US Remote; role is intended for US-based candidates

Salary: $330,000–$360,000 annual salary for US-based candidates; equity may also be offered. Candidates outside the US may receive a location-specific range from the recruiter.

Company

Hims & Hers is a public health and wellness platform delivering personalized healthcare from diagnosis through treatment and delivery.

What you will do

• Lead and grow teams of ML engineers, applied scientists, and ML production engineers building AI services from problem framing through production operation.
• Set the technical strategy for LLM applications, including prompt and context design, retrieval, tool calling, agentic workflows, structured outputs, fallbacks, latency, and cost management.
• Direct the orchestration, validation, guardrails, and deterministic scaffolding required for dependable and auditable AI outputs.
• Guide development of deep learning and classical ML models for clinical, recommendation, ranking, classification, and prediction use cases.
• Define production standards for accuracy, latency, cost, reliability, rollout strategy, evaluation, feedback loops, and ownership.
• Partner with Clinical, Medical Affairs, Product, Data Science, Engineering, Security, Legal, and Compliance stakeholders while shaping AI strategy and multi-year investment decisions.

Requirements

• 14+ years of experience in machine learning and software engineering, including 8+ years leading ML teams.
• Experience managing managers or senior technical leads and developing senior individual contributors and managers.
• Track record of shipping and operating ML-powered products at scale, beyond prototypes or research.
• Strong understanding of LLM application development, including RAG, prompt engineering, fine-tuning, evaluation, agents, and tool-calling architectures.
• Experience training and deploying deep learning models and making trade-offs among model quality, latency, cost, and operational complexity.
• Excellent communication skills and experience influencing executives, peers, and clinical stakeholders.

Nice to have

• Healthcare, digital health, regulated-domain, or safety-critical ML experience.
• Experience with clinical decision support, clinical NLP, or ML systems used by human experts.

Culture & Benefits

• Focus on ethics, wellness, inclusion, and a strong sense of belonging.
• Flexible and remote work approach.
• Comprehensive total rewards package that may include equity.
• Reasonable accommodations are available for qualified individuals with disabilities and disabled veterans.