A Research Engineer in the Reinforcement Learning teams at Anthropic, based in London, who blends research and engineering responsibilities to advance the capabilities and safety of large language models. The role involves designing and optimizing RL infrastructure, creating novel training environments, improving model reasoning, and building scalable systems to support cutting‑edge research.
Research Engineer, Machine Learning (Reinforcement Learning) at Anthropic
Hybrid - London, UK
More jobs at AnthropicSalary
GBP 260,000 - 630,000
Requirements
Skills
- Proficient in Python and async/concurrent programming with frameworks like Trio
- Experience with machine learning frameworks (PyTorch, TensorFlow, JAX)
- Industry experience in machine learning research
- Ability to balance research exploration with engineering implementation
- Enjoy pair programming
- Strong focus on code quality, testing, and performance
- Strong systems design and communication skills
- Passion for the potential impact of AI and commitment to developing safe and beneficial systems
- Familiarity with LLM architectures and training methodologies
- Experience with reinforcement learning techniques and environments
- Experience with virtualization and sandboxed code execution environments
- Experience with Kubernetes
- Experience with distributed systems or high-performance computing
- Experience with Rust and/or C++
Responsibilities
- Architect and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters
- Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents
- Drive performance improvements across the stack through profiling, optimization, and benchmarking; implement efficient caching solutions and debug distributed systems
- Collaborate across research and engineering teams to develop automated testing frameworks, design clean APIs, and build scalable infrastructure
Technologies
PythonTrioPyTorchTensorFlowJAXKubernetesRustC++GPU clustersDistributed systemsVirtualizationSandboxed code execution environments
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