Research Engineer, Machine Learning (Horizons)
London, UK
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We aim for AI to be safe and beneficial for users and society. Our team is a growing group of researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role:
As a Research Engineer on the Reinforcement Learning Fundamentals team, you will collaborate with researchers and engineers to advance the capabilities and safety of large language models through fundamental research in reinforcement learning, enhancing reasoning abilities in areas like code generation and mathematics, and exploring reinforcement learning for agentic / open-ended tasks.
Representative projects:
- Develop and implement novel reinforcement learning techniques to improve the performance and safety of large language models.
- Create tools and environments for models to interact with, enabling complex, open-ended tasks.
- Design and conduct experiments to enhance models' reasoning capabilities, especially in code generation and mathematics.
You may be a good fit if you:
- Have 5+ years of industry-related experience
- Are proficient in Python and experienced with deep learning frameworks such as PyTorch or Jax
- Possess a strong software engineering background and enjoy working closely with researchers and engineers
- Enjoy pair programming
- Care about code quality, testing, and performance
- Are passionate about AI's potential impact and committed to developing safe, beneficial systems
Strong candidates may also:
- Have a background in machine learning, reinforcement learning, or high-performance computing
- Have experience with virtualization and sandboxed code execution environments
- Have experience with Kubernetes
- Have contributed to open-source projects or published research papers in relevant fields
Candidates need not have:
- Formal certifications or educational credentials
- Prior experience with LLMs or machine learning research
Deadline to apply:Rolling review; no fixed deadline.
The expected salary range is provided separately.
Logistics
Education:Bachelor's degree or equivalent experience in a related field.
Location-based hybrid policy:Expectation of being in the office at least 25% of the time; some roles may require more.
Visa sponsorship:We sponsor visas when possible; we will make reasonable efforts to assist if you are offered the role.
We encourage applicants from diverse backgrounds and those who may not meet every qualification to apply.
How we're different
We focus on big science and impactful research, valuing collaboration, communication, and impact in AI safety and steerability. Our research directions include GPT-3, interpretability, multimodal neurons, scaling laws, and more.
Come work with us!
Based in San Francisco, we offer competitive compensation, benefits, flexible hours, and a collaborative environment.
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