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Research Engineer, Computer Use

On-site
AnthropicSan Francisco, CA, US / Seattle, WA, US1 month agoWebsite
ActiveRecently funded
AI Research & Engineering

Compensation

$500,000-$850,000/yr
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Description

About the role

The Computer Use team focuses on teaching Claude to see, use, and understand computer interfaces. As a Research Engineer on the team, you'll work on advancing our models' ability to reliably and safely operate real software. We're looking for someone who's genuinely excited about both the research and the product sides of computer use.

Your work will translate directly into model improvements in our own and our customers' products. You can try Claude's computer use capabilities today through the Claude in Chrome extension and Claude Cowork.

Key Responsibilities:

  • Design and run experiments to improve Claude's perception and agentic capabilities
  • Develop robust, reliable evaluation frameworks for measuring our models' ability to complete complex computer tasks
  • Build and improve computer use and vision reinforcement learning training environments
  • Create pipelines and tools to test and validate complex RL environments
  • Collaborate with teams across the model training and infrastructure stack to improve our production training setup
  • Partner with product teams to bring research advances into production

Minimum Qualifications:

  • Software engineering experience and proficiency in Python
  • Experience training, fine-tuning, or evaluating machine learning models
  • Strong communication skills and a collaborative working style
  • Care about the societal impacts and safety of your work

Preferred Qualifications:

  • Experience training models for computer use or other agentic capabilities
  • Experience with reinforcement learning, particularly in long-horizon or sparse-reward settings
  • Familiarity with multimodal model training
  • Experience building evaluations or benchmarks for agentic systems
  • Experience building reinforcement learning environments, simulation systems, or large-scale ML infrastructure
  • Experience working closely with product teams to drive model improvements

Stack

PythonAgentic AIMachine LearningFine-tuningReinforcement LearningMultimodal
Posted
Jun 30, 2026
Last seen
Jul 1, 2026
First seen
Jul 1, 2026

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