Research Engineer, Knowledge Team

Anthropic is seeking a Research Engineer to join their Knowledge Team in London, focusing on revolutionizing how their AI system Claude interacts with external data sources. This role sits at the intersection of software engineering and machine learning research, requiring expertise in both areas.

The position involves redesigning fundamental approaches to information architecture, specifically optimized for LLM consumption rather than traditional human-centric designs. Key responsibilities include implementing novel information architecture strategies, conducting finetuning and reinforcement learning to enhance language model capabilities, and developing sophisticated evaluation frameworks for knowledge base interactions.

The ideal candidate will be an accomplished Python developer with substantial machine learning research experience, particularly in working with Large Language Models. They should have a track record of building complex AI systems and distributed information retrieval architectures. The role demands both technical excellence and strong communication skills, as collaboration with world-class ML researchers is a crucial aspect of the position.

Anthropic offers a compelling compensation package ranging from £250,000 to £340,000 GBP annually, along with comprehensive benefits including equity options, flexible working arrangements, and generous leave policies. The company operates on a hybrid work model requiring at least 25% office presence in their London location.

What makes this opportunity unique is Anthropic's approach to AI research as "big science," focusing on large-scale, cohesive research efforts rather than smaller, isolated projects. The company values impact-driven work aimed at developing steerable, trustworthy AI systems, and maintains a highly collaborative environment with frequent research discussions.

This role offers the chance to work on cutting-edge AI technology while contributing to Anthropic's mission of ensuring AI systems are safe and beneficial for society. The position combines technical challenges with meaningful impact, making it ideal for engineers who want to push the boundaries of AI capabilities while maintaining a focus on ethical considerations and societal implications.