Anthropic
Technical Program Manager, Research
$365K–$435K
San Francisco, CA +2 · Manager · Full-time · Posted Apr 29, 2026
- Location
- San Francisco, CA
New York City, NY
San Francisco, California, United States - Experience
- Several years of experience building technical programs from scratch is described as an ideal fit; the posting says required years correlate with internal job level requirements.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; relevant field of study demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; Anthropic says it will make every reasonable effort to obtain a visa after an offer.
About the job
Build and lead cross-functional programs, processes, and tooling that help research teams execute complex AI research initiatives across changing domains.
What you'll do
- Identify high-leverage research team needs and drive ambiguous, cross-team initiatives from planning through execution.
- Develop compute planning, model evaluation readiness, and RL environment operations across research and production workstreams.
- Establish effective processes and tooling, and advise research leadership on technical tradeoffs and decisions.
What they ask for
- Background in ML research or engineering, with experience building technical programs from scratch.
- Track record of operational ownership of complex technical systems, including monitoring, incident response, and performance optimization.
- Ability to reason about technical tradeoffs and communicate actionable recommendations to leadership.
- Strong stakeholder management and ability to influence senior technical staff.
Nice to have
- Hands-on exposure to training, evaluation, or large-scale distributed systems.
Pay
$365,000 — $435,000 USD (base salary)
Tools
ML, compute, evals, RL environments, model architecture, training infrastructure
AI focus
Create safe and beneficial AI systems; support research across model development, compute, evaluations, RL environments, and emerging initiatives.
Model-written summary · the original posting is authoritative