# Research Engineer, Computer Use

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA, New York, NY, Seattle, WA
**Role:** ML Engineering
**Salary:** $500k – $850k/yr
**Experience:** 5+ years
**Skills:** Python, Machine Learning, Reinforcement Learning, Multimodal Models, Rl Environments, Model Training, Model Evaluation, Model Fine-Tuning, Agentic Systems, Benchmarks, ML Infrastructure
**Posted:** 2026-06-30

> Research Engineer advancing Claude's computer use capabilities through experiments, RL environments, evaluations, and infrastructure for perception and agentic tasks. Requires Python, ML training/evaluation experience, and a focus on safe AI.

## Job Description

## 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

## Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience in a field relevant to the role

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