Research Engineer, Knowledge Team
Designs new information architectures for LLMs to interact with external data sources, implements finetuning/RL training, builds evaluation sets, and develops agentic search capabilities. Requires strong Python/ML skills and LLM experience.
About the job
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
- Very experienced Python programmer who can quickly produce 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
- Pick up slack, even if it goes outside your job description
- Enjoy pair programming
- 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
Nice-to-Haves
- 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
Compensation
Annual Salary: $350,000—$850,000 USD
Skills
Python, Machine Learning, LLMs, Fine-Tuning, Reinforcement Learning, RAG, Knowledge Graphs, Agentic Systems, Information Retrieval, Distributed Data Processing
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