Research Engineer, Computer Use

Details

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

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.

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

Requirements

• 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

Logistics

• 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.