Senior Director, Machine Learning

hims & hers

. Lead and grow ML engineers, applied scientists, and ML production engineers building AI services end to end .

Posted 9/29/2026full-timeRemote • United StatesSenior💰 $330,000 - $360,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in leading machine learning teams and developing AI services, with a strong focus on modern LLM application development, deep learning model training, and operational management of ML-powered products. Proven ability to establish production standards, collaborate across functions, and shape strategic AI roadmaps.

Highest-signal resume keywords

Machine Learning LeadershipLLM Application DevelopmentDeep Learning Model TrainingAI Service Production StandardsCross-Functional Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningLLM Application DevelopmentPrompt EngineeringModel EvaluationSoftware ArchitectureModel TrainingOperational ManagementExperiment DesignCode Quality

Soft Skills

Excellent Communication

Industry Keywords

HealthcareDigital HealthRegulated DomainsClinical Decision SupportClinical NLP

About the role

Key responsibilities & impact

Lead and grow ML engineers, applied scientists, and ML production engineers building AI services end to end
Own strategy for building on frontier LLMs, including prompt and context design, retrieval, tool and function calling, agentic workflows, structured output reliability, fallback behavior, latency, and cost management
Design orchestration, validation, guardrails, and deterministic scaffolding around LLM calls
Direct development of in-house deep learning and classical ML models for clinical and recommendation use cases
Set production standards for AI services, including accuracy, latency, cost, graceful failure, rollout strategy, and ownership
Make build-versus-fine-tune-versus-prompt decisions
Partner with Clinical and Medical Affairs on oversight, validation, and human-in-the-loop design
Partner with ML infrastructure and evaluation teams on evaluation criteria, feedback loops, annotation needs, and metrics
Collaborate with Product, Data Science, Engineering, Security, Legal, and Compliance
Establish standards for experiment design, model documentation, reproducibility, code quality, and responsible AI
Build hiring, leveling, and mentorship practices; develop senior individual contributors and managers
Shape multi-year AI roadmap and investment decisions and represent AI strategy to executive leadership

Requirements

What you’ll need

14+ years of experience in machine learning and software engineering
8+ years leading ML teams
Experience managing managers or senior tech leads
Track record of shipping ML-powered products to production at scale and owning them operationally
Depth in modern LLM application development, including RAG, prompt engineering, fine-tuning and adaptation, evaluation, agent and tool-calling architectures, and practical limitations
Experience training and deploying deep learning models, including recommendation, ranking, classification, or sequence models
Strong software architecture judgment regarding service boundaries, data flow, failure modes, and cost
Experience balancing model quality against latency, cost, and operational complexity
Ability to turn ambiguous, high-value problems into shipped systems with measurable impact
Excellent communication skills 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 used by human experts
Legally authorized to work in the U.S. without restriction for any employer
Must not require immigration sponsorship by Hims & Hers to work in the U.S.

Benefits

Comp & perks

Equity grant may be included in the Total Rewards package
Flexible/remote work approach
Reasonable accommodations for qualified individuals with disabilities and disabled veterans
Diverse, ethical, wellness-focused, and belonging-oriented workplace