Research Engineer, Computer Use

United States Digital Space LLC; San Francisco (CA); Hybrid; USD 500,000 - 850,000; Full time

Job summary

United States Digital Space LLC in San Francisco is seeking a Research Engineer to enhance AI system capabilities through innovative research and development. The role involves designing experiments, developing evaluation frameworks, and collaborating with cross-functional teams to implement improvements into production.

The ideal candidate has a Bachelor's degree, strong software engineering skills, and experience with machine learning. The position offers a hybrid work model and a competitive salary range of $500,000–$850,000 annually.

Qualifications

• Experience in training, fine-tuning, or evaluating machine learning models.
• Concern for the societal impacts and safety of your work.

Responsibilities

• Design and run experiments to improve Claude's capabilities.
• Develop evaluation frameworks for measuring complex task completion.
• Build and improve reinforcement learning training environments.
• Create pipelines to test and validate RL environments.
• Collaborate with teams to improve production training setup.
• Partner with product teams to translate research into production.

Skills

Software engineering experience

Proficiency in Python

Experience training machine learning models

Strong communication skills

Collaborative working style

Concern for societal impacts of work

Education

Bachelor’s degree or equivalent experience

Job description

About the company

The company’s mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for our users and society. Our team is a rapidly growing group of researchers, engineers, policy experts, and business leaders building beneficial AI.

About the role

The Computer Use team focuses on teaching Claude to see, use, and understand computer interfaces. As a Research Engineer, you’ll work on advancing our models' ability to reliably and safely operate real software and help translate research into product improvements.

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.
• Concern for the societal impacts and safety of your work.

Preferred Qualifications

• Experience training models for computer use or other agentic capabilities.
• Experience with reinforcement learning, especially 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.

Annual Salary

$500,000–$850,000 USD.

Logistics

Minimum education: Bachelor’s degree or equivalent 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.

Location‑based hybrid policy: Staff expected to be at one of our offices at least 25% of the time; some roles may require more time in‑office.

Visa sponsorship: We sponsor visas when possible.

We encourage applicants from underrepresented groups to apply. We value diversity and strive to include a range of perspectives.