Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
Agentic Systems @ 3
Communication @ 3
LLM @ 3
Machine Learning @ 3
Python @ 3
RAG @ 3
Reinforcement Learning
Search Engines @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic is looking for Research Engineers to help redesign how Claude interacts with external data sources. The role involves designing new architectures for organizing information and training language models to optimally use those architectures.
Responsibilities
- Design and implement new information architecture strategies from scratch.
- Perform fine-tuning and reinforcement learning to teach language models how to interact with new information architectures.
- Build challenging knowledge-base evaluation sets to identify failure modes in how language models work with external data.
- Design and evaluate advanced agentic search capabilities.
Requirements
- Extensive Python programming experience, with the ability to quickly produce reliable, high-quality code.
- Machine learning research experience.
- Experience developing software that uses large language models such as Claude.
- Results-oriented approach, with flexibility and a focus on impact.
- Willingness to take on work beyond the formal job description.
- Enjoyment of pair programming.
- Interest in partnering with ML researchers to develop new LLM capabilities.
- Awareness of the societal impacts of AI-related work.
- Clear written and verbal communication skills.
Strong candidates may also have experience with:
- Collaborating with product teams to prototype and deliver innovative solutions quickly.
- Building complex agentic systems that use LLMs.
- Developing scalable distributed information retrieval systems, including search engines, knowledge graphs, retrieval-augmented generation (RAG), indexing, ranking, query understanding, and distributed data processing.
A bachelor's degree or an equivalent combination of education, training, and experience is required. The required field of study must be relevant to the role, as demonstrated through coursework, training, or professional experience. Required years of experience correlate with the internal job level requirements.
Work Arrangement
This is a remote-friendly role with travel required. Staff are currently expected to work from one of Anthropic's offices at least 25% of the time, although some roles may require more office time.
Benefits
Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and an office space for collaboration.