Research Engineer (Computer Use)

Anthropic Limited
New York, NY, United States
28 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Computer Literacy Python (Programming Language) Software Engineering Reinforcement Learning Machine Learning Operations

Job description

  • 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
  • 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

Skills & expertise Observation skills Communication skills Collaboration and teamwork, * Strong communication skills and a collaborative working style

  • Experience training, fine-tuning, or evaluating machine learning models
  • Care about the societal impacts and safety of your work
  • Software engineering experience and proficiency in Python
  • Experience training models for computer use or other agentic capabilities
  • Experience building reinforcement learning environments, simulation systems, or large-scale ML infrastructure
  • Familiarity with multimodal model training
  • Experience building evaluations or benchmarks for agentic systems
  • Experience with reinforcement learning, particularly in long-horizon or sparse-reward settings
  • Experience working closely with product teams to drive model improvements
  • Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
  • Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
  • Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
  • We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed

Benefits & conditions

  • Comprehensive health, dental, and vision insurance for you and your dependents
  • Inclusive fertility benefits via Carrot Fertility
  • 22 weeks of paid parental leave
  • Flexible paid time off and absence policies
  • Mental health support for you and your dependents
  • Competitive salary and equity packages
  • Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
  • Retirement plans with competitive matching
  • Life and income protection plans
  • $500/month flexible wellness and time saver stipend
  • Commuter benefits
  • Annual education stipend
  • Home office stipends
  • Relocation support for those moving for Anthropic
  • Daily meals and snacks in the office

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on job-boards.greenhouse.io

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:45 min

Supervised, unsupervised, and reinforcement learning paradigms explained

Alexandra Waldherr · LIVE

1:22 min

Understanding software engineering as more than just coding

Lilia Gargouri Lilia Gargouri · WWC Europe 2026

3:42 min

Addressing educational gaps and retaining early female technological talent

Rudi Bauer Rudi Bauer +1 · Cappuccino with HR

4:45 min

Elevating engineering roles through targeted skill augmentation

Lee Faus · Coffee With Developers

2:06 min

Understanding supervised, unsupervised, and reinforcement learning models

Lutske van der Meer Lutske van der Meer · WWC 2024

1:29 min

Undervaluing product design by treating software engineers as generic programmers

Marlene Roth Marlene Roth +1 · WWC 2025

Videos

See all

Related articles

See all