Anthropic
Research Engineer / Research Scientist, RL Frontiers
$500K–$850K
San Francisco, CA +3 · Full-time · Posted Sep 29, 2026
- Location
- San Francisco, CA
New York City, NY
Seattle, WA
San Francisco, California, United States - Experience
- Years of experience required will correlate with the internal job level requirements for the position.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; relevant field demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; the company will make every reasonable effort to obtain a visa after an offer.
About the job
Develop and scale reinforcement-learning algorithms, model architectures, and research systems for large language models, and diagnose performance and training issues in frontier-scale runs.
What you'll do
- Study RL training and sampling efficiency as models, context lengths, and compute scale; develop algorithmic and systems improvements.
- Develop architectures and RL algorithms, scale promising results to large runs, and investigate differences, instability, and performance regressions.
- Build experimental infrastructure and performance and cost models; own end-to-end performance of large RL runs.
What they ask for
- Deep familiarity with transformer language models, their architecture, training dynamics, and large-scale optimization.
- Hands-on experience training large models in distributed settings, including data, tensor, and pipeline parallelism.
- Track record of original technical work in ML training or systems, demonstrated through research, open-source, or production impact.
- Strong Python and JAX or PyTorch programming skills; ability to design rigorous large-scale experiments and reason quantitatively about compute, memory, and communication costs.
Nice to have
- Research experience in reinforcement learning, optimization, or large-scale training; experience developing RL algorithms for language models.
- Experience with scaling laws, transformer architecture changes, large accelerator fleets, training numerics, GPU or TPU performance, C++ or Rust.
Pay
$500,000 — $850,000 USD annual base salary
Tools
Python, JAX, PyTorch, C++, Rust, GPU, TPU
AI focus
Develop and scale reinforcement learning methods and architectures for language models, including investigation of training dynamics and efficiency at frontier scale.
Model-written summary · the original posting is authoritative