Anthropic
Staff+ Research Engineer, RL Data Platform
$500K–$850K
San Francisco, CA +3 · Staff · Full-time · Posted Aug 27, 2026
- Location
- San Francisco, CA
New York City, NY
New York, New York, United States
San Francisco, California, United States - Experience
- Years required correlate with internal job level requirements; no specific number stated.
- 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; if an offer is made, Anthropic will make every reasonable effort to obtain a visa.
About the job
Builds and operates full-stack systems for collecting, processing, and serving human feedback and other data used to train Claude, partnering with RL researchers to deliver reliable data pipelines and tools.
What you'll do
- Build and operate annotator and researcher interfaces, backend services, APIs, and data pipelines.
- Own system reliability, latency, usability, monitoring, and inspection tools.
- Work with RL researchers to scope data collection campaigns and remove bottlenecks to getting data into training.
What they ask for
- Production full-stack experience with TypeScript/React and Python.
- Experience designing and operating backend services and data pipelines relied on by other teams.
- Track record of owning projects end-to-end, from ambiguous brief to production.
- Effective use of AI tools in day-to-day work.
Nice to have
- Experience building human-in-the-loop data tooling or human-feedback pipelines for ML systems.
- Experience with researcher-facing tools, data-collection experiments, crowdworker or expert vendor platforms, or familiarity with LLM training and evaluation.
Pay
$500,000–$850,000 USD annual base salary
Tools
TypeScript, React, Python
AI focus
Builds data-collection and feedback systems that support RL training of Claude; the posting also requires effective use of AI tools in day-to-day work.
Model-written summary · the original posting is authoritative