Research Engineer, Knowledge Team

Position Overview

• Location Type: Hybrid
• Job Type: Full-time
• Salary: $315,000 - $560,000 USD (Annual)

Anthropic's 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.

This role focuses on redesigning how Claude interacts with external data sources. Many paradigms for organizing data and knowledge bases assume human consumers and constraints, which is no longer true for LLMs. The Research Engineer will design new architectures for information organization and train language models to optimally use these architectures.

Requirements

• Very experienced Python programmer capable of producing reliable, high-quality code.
• Good machine learning research experience.
• Experience developing software that utilizes Large Language Models such as Claude.
• Results-oriented with a bias towards flexibility and impact.
• Willingness to pick up slack, even if it goes outside the job description.
• Enjoyment of pair programming.
• Desire to partner with world-class ML researchers to develop new LLM capabilities.
• Care about the societal impacts of your work.
• Clear written and verbal communication.
• Education: Bachelor's degree in a related field or equivalent experience.

Strong candidates will also have experience with:

• Collaborating with product teams to quickly prototype and deliver innovative solutions.
• Building complex agentic systems that utilize LLMs.
• Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing.

Responsibilities

• Designing and implementing new information architecture strategies from scratch.
• Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures.
• Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data.
• Designing and evaluating advanced agentic search capabilities.

Logistics

• Location-based hybrid policy: Expect to be in one of our offices at least 25% of the time. Some roles may require more time in our offices.
• Visa sponsorship: Anthropic sponsors visas and will make every reasonable effort to secure a visa if an offer is made.

About Anthropic

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. 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.

Application Instructions

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.