Research Engineer, Knowledge Team
About the role
We are looking for Research Engineers to help us redesign how Claude interacts with external data sources. Your job will be to design new architectures for how information is organized, and train language models to optimally use those architectures.
Responsibilities
- Designing and implementing from scratch new information architecture strategies
- 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
Requirements
- A very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using
- 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
- Pick up slack, even if it goes outside your job description
- Enjoy pair programming (we love to pair!)
- Want 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
Qualifications
- 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
Skills
- Experience with Large Language Models (LLMs) such as Claude
- Experience with Python programming
- Experience with machine learning research
- Experience with distributed information retrieval systems
Benefits
The annual compensation range for this role is listed below. For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary $350,000—$850,000 USD
Pay
The annual compensation range for this role is listed below. For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary $350,000—$850,000 USD
Schedule
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Location-based hybrid policy
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
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. 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.
How We're Different
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. As such, we greatly value communication skills. 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. Come work with us!
Guidance on Candidates' AI Usage
Learn about our policy for using AI in our application process.