Research Engineer, Machine Learning (Horizons) London, UK
Anthropics mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
As a Research Engineer on the Reinforcement Learning Fundamentals team, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models through fundamental research in reinforcement learning, improving reasoning abilities in areas such as 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.
Design and run experiments to enhance models' reasoning capabilities, particularly in code generation and mathematics.
Are proficient in Python and have experience with deep learning frameworks such as PyTorch or Jax
Have a strong software engineering background and are interested in working closely with researchers and other engineers
Enjoy pair programming (we love to pair!)
Care about code quality, testing, and performance
Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems
Have a strong background in machine learning, reinforcement learning, or high performance computing
Have contributed to open-source projects or published research papers in relevant fields
Experience with LLMs or machine learning research before
We require at least a Bachelor's degree in a related field or equivalent experience.
Location-based hybrid policy: Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact advancing our long-term goals of steerable, trustworthy AI rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
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While we encourage people to use AI systems during their role to help them work faster and more effectively, please do not use AI assistants during the application process. We want to understand your personal interest in Anthropic without mediation through an AI system, and we also want to evaluate your non-AI-assisted communication skills. Examples could include past work, volunteering, civic engagement, community organizing, donations, family support, etc. *
Whats your ideal breakdown of your time in a working week, in terms of hours or % per week spent on meetings, coding, reading papers, etc.?
Will you now or will you in the future require employment visa sponsorship to work in the country in which the job you're applying for is located? * Are you open to relocation for this role? * If you would need to relocate, please type relocating.
