Research Engineer, Computer Use

Anthropic; San Francisco (CA); Hybrid; USD 500,000 - 850,000; Full time

Job summary

Anthropic Limited is seeking a Research Engineer for the Computer Use team to advance Claude's ability to see, use, and understand software. You will work on real models, run experiments, and contribute to production systems.

This role blends research and practical product impact, with collaboration across training and infra, and opportunities to shape safety and reliability at scale.

Qualifications

• Software engineering experience with Python.
• Experience training, fine-tuning, or evaluating ML models.
• Strong communication and collaborative working style.
• Care about the societal impacts and safety of your work.

Responsibilities

• Design and run experiments to improve Claude's perception and agentic abilities.
• Develop robust evaluation frameworks for complex ML tasks.
• Build RL training environments for computer use and vision.
• Create pipelines and tools to test RL environments.
• Collaborate with model training and infrastructure teams to improve production setups.
• Partner with product teams to translate research into production.

Skills

Python

ML training

Communication

Safety focus

Education

Bachelor's degree

Field relevant to AI/ML

Job description

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 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.

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

The annual compensation range for this role is listed below.

Annual Salary

$500,000—$850,000 USD

Logistics

Minimum education:

Bachelor's degree or an equivalent combination of education, training, and/or experience

Required field of study:

A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience:

Years of experience required will correlate with the internal job level requirements for the position

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.

Your safety matters to us.

To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

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.

Guidance on Candidates' AI Usage:

Learn about our policy for using AI in our application process.