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Research Engineer / Research Scientist, RL Frontiers

Anthropic· AI Research & Engineering
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Hybrid (San Francisco, CA), Hybrid (New York City, NY), Hybrid (Seattle, WA)$500k - $850kFull-timePosted 3w ago

About the role

Role focusing on reinforcement learning at scale, developing architectures and algorithms, and building systems for frontier-scale RL experiments at Anthropic.

Responsibilities

  • Study how RL training and sampling scale with model size, context length, and compute, and find the algorithmic and systems changes that keep scaling efficient
  • Develop next-generation model architectures and RL algorithms, and make them run efficiently at frontier scale
  • Take promising small-scale results to frontier-scale runs, and diagnose why they behave differently when they get there, whether the cause is numerical, algorithmic, or systemic
  • Build the experimental infrastructure that sets research velocity: fast, reproducible comparisons of architecture and algorithm variants at meaningful scale
  • Own end-to-end performance of our largest RL runs, from research code down to the hardware
  • Build performance and cost models for proposed architecture and algorithm changes, and use them to decide which ideas get scaled
  • Investigate training dynamics at scale, including instabilities, divergence, and throughput regressions, and trace them to root cause

Qualifications

  • Deep familiarity with modern transformer language models, including their architecture, training dynamics, and the behavior of large-scale optimization
  • Hands-on experience training large models in a distributed setting, including the tradeoffs between data, tensor, and pipeline parallelism
  • A track record of original technical work in ML training or systems, such as new methods, architectures, or optimizations, demonstrated through research, open-source, or production impact
  • Ability to design rigorous experiments at scale, including baselines, ablations, and enough statistical care to trust a result that costs real compute
  • Ability to reason quantitatively about the compute, memory, and communication costs of a model or algorithm
  • Strong programming skills in Python and JAX or PyTorch, and comfort reading and changing code at every layer of the stack

Skills

Required:Transformer language modelsDistributed model trainingExperiment design at scalePython, JAX or PyTorch

Benefits

  • Competitive compensation and benefits
  • Optional equity donation matching
  • Generous vacation and parental leave
  • Flexible working hours
  • Lovely office space
Last updated Sep 30, 2026. Interested? Apply on the company site.

About Anthropic

building reliable, interpretable, and steerable AI systems

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

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