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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Research Engineer, Machine Learning (Reinforcement Learning) - **Company:** Anthropic - **Location:** Greater London, UK - **Salary:** £260,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Computer Clusters, Software Quality, Concurrent Computing, Software Debugging, Distributed Systems, Python (Programming Language), Machine Learning, Pair Programming, Tensorflow, Virtualization Technology, Reinforcement Learning, High Performance Computing, Pytorch, Large Language Models, Kubernetes - **Published:** August 26, 2026 - **Apply:** https://www.collegerecruiter.com/job/2815064184-research-engineer-machine-learning-reinforcement-learning ## About the Role * Proficient in Python and async/concurrent programming frameworks like Trio. * Experience with machine-learning frameworks (PyTorch, TensorFlow, JAX). * Industry experience in ML research. * Can balance research exploration with engineering implementation. * Enjoy pair programming. * Care about code quality, testing, and performance. * Strong systems design and communication skills. * Passionate about AI impact and committed to 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 or C++. Strong Candidates Do Not Need * Formal certifications or specific education credentials. * Academic research experience or publication history., * Minimum education: Bachelor's degree or equivalent. * Required field of study: Relevant to the role. * Minimum years of experience: Depends on internal level. * Location-based hybrid policy: Staff should be in office at least 25% of time. * Visa sponsorship: We sponsor visas when possible. ## Description About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. About the Role As a Research Engineer within Reinforcement Learning, you will collaborate with researchers and engineers to advance the capabilities and safety of large language models. The role blends research and engineering: implement novel approaches while contributing to research direction. Representative Projects * Architect and optimize core reinforcement learning infrastructure, including training abstractions and distributed experiment management across GPU clusters. * Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents. * Drive performance improvements through profiling, optimization, and benchmarking; implement efficient caching and debug distributed systems. * Collaborate with research and engineering teams to develop automated testing frameworks, clean APIs, and scalable infrastructure. You May Be a Good Fit If * Proficient in Python and async/concurrent programming frameworks like Trio. * Experience with machine-learning frameworks (PyTorch, TensorFlow, JAX). * Industry experience in ML research. * Can balance research exploration with engineering implementation. * Enjoy pair programming. * Care about code quality, testing, and performance. * Strong systems design and communication skills. * Passionate about AI impact and committed to safe and beneficial systems. Strong Candidates May Also Have * 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 or C++. Strong Candidates Do Not Need * Formal certifications or specific education credentials. * Academic research experience or publication history. Logistics * Annual Salary: £260,000-£630,000 GBP. * Minimum education: Bachelor's degree or equivalent. * Required field of study: Relevant to the role. * Minimum years of experience: Depends on internal level. * Location-based hybrid policy: Staff should be in office at least 25% of time. * Visa sponsorship: We sponsor visas when possible. ## Related Videos - [AI in the Open and in Browsers - Tarek Ziadé](https://www.wearedevelopers.com/videos/1787-ai-in-the-open-and-in-browsers-tarek-ziade) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)