Skip to content
AnthropicAnthropicSan Francisco, CA

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.

350k – 850k
HybridML Engineering

About the role

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

PythonMachine LearningLLMsFine-TuningReinforcement LearningRAGKnowledge GraphsAgentic SystemsInformation RetrievalDistributed Data Processing

Similar roles

ML Engineering jobs
Thinking Machines Lab

Research Infrastructure Engineer

Thinking Machines LabSan Francisco, CA

Build and operate research infrastructure like evaluation frameworks, RL training systems, and experiment tracking platforms. Partner directly with ML researchers to identify bottlenecks, ensure high adoption of tools, and accelerate research velocity.

350k – 475k
On-siteML Engineering
Anthropic

Research Engineer, Safeguards Labs

AnthropicSan Francisco, CA +1

Research engineer on the Safeguards Labs team building and evaluating novel safety methods to detect misuse, strengthen model safeguards, and reduce real-world harm from Claude.

350k – 850k
HybridML Engineering
Thinking Machines Lab

Research, Vision Expertise

Thinking Machines LabSan Francisco, CA

Conducts research on visual perception, multimodal learning, and large-scale AI model training. Designs architectures, builds datasets and evaluations, and collaborates on frontier models. Requires ML expertise, Python proficiency, and experimental rigor.

350k – 475k
On-siteML Engineering
Thinking Machines Lab

Research, Pre-Training Data

Thinking Machines LabSan Francisco, CA

Designs and implements methods for sourcing, curating, and analyzing large-scale pre-training datasets for AI models, blending research with production-grade data engineering. Requires Python proficiency, deep learning frameworks, and strong ML fundamentals.

350k – 475k
On-siteML Engineering
Thinking Machines Lab

Research, Post-Training Data

Thinking Machines LabSan Francisco, CA

Conducts post-training research for AI models, designing data collection strategies, developing labeling pipelines, modeling human preferences, and iterating on evaluations to improve model alignment, reasoning, and helpfulness. Requires strong Python skills, ML framework proficiency, and experimental rigor.

350k – 475k
On-siteML Engineering