Senior Director, Machine Learning

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead and expand a team of ML engineers, applied scientists, and ML production engineers in developing AI services from inception to deployment.

• Take ownership of the strategy for leveraging cutting-edge LLMs, encompassing prompt and context design, retrieval, tool and function invocation, agentic workflows, structured output reliability, fallback behavior, latency, and cost management.

• Design orchestration, validation, guardrails, and deterministic frameworks for LLM interactions.

• Oversee the development of proprietary deep learning and classical ML models aimed at clinical and recommendation applications.

• Establish production benchmarks for AI services, including accuracy, latency, cost, graceful failure, rollout strategies, and ownership responsibilities.

• Make strategic decisions regarding building, fine-tuning, or prompting models.

• Collaborate with Clinical and Medical Affairs for oversight, validation, and human-in-the-loop design processes.

• Work alongside ML infrastructure and evaluation teams to define evaluation criteria, feedback loops, annotation requirements, and metrics.

• Partner with Product, Data Science, Engineering, Security, Legal, and Compliance teams.

• Set standards for experiment design, model documentation, reproducibility, code quality, and responsible AI practices.

• Develop hiring practices, leveling, and mentorship programs; foster the growth of senior individual contributors and managers.

• Shape a multi-year AI roadmap and investment decisions while representing the AI strategy to executive leadership.

⛳️ Requirements

• Over 14 years of experience in machine learning and software engineering.

• More than 8 years of experience leading ML teams.

• Proven experience managing managers or senior technical leads.

• A strong track record of delivering ML-powered products to production at scale and overseeing their operational aspects.

• Extensive knowledge in modern LLM application development, including RAG, prompt engineering, fine-tuning and adaptation, evaluation, agent and tool-calling architectures, and practical constraints.

• Experience in training and deploying deep learning models, such as recommendation, ranking, classification, or sequence models.

• Strong judgment in software architecture regarding service boundaries, data flow, failure modes, and cost considerations.

• Ability to balance model quality with latency, cost, and operational complexity.

• Capability to transform ambiguous, high-value problems into implemented systems with measurable outcomes.

• Exceptional communication skills for engaging with peers, executives, and clinical stakeholders.

• Bonus: experience in healthcare, digital health, regulated domains, or safety-critical ML systems.

• Bonus: experience with clinical decision support, clinical NLP, or ML systems utilized by human experts.

• Must be legally authorized to work in the U.S. without restrictions for any employer.

• Must not require immigration sponsorship from Hims & Hers to work in the U.S.

🏝️ Benefits

• Equity grant may be part of the Total Rewards package.

• Flexible and remote work options available.

• Reasonable accommodations provided for qualified individuals with disabilities and disabled veterans.

• A diverse, ethical, wellness-focused, and inclusive workplace environment.