Join Anthropic as a Research Engineer to enhance AI's ability to understand and operate software, contributing to impactful AI systems.
Posted by employer 3 months ago
First seen on Joblaze 3 months ago
Last verified on the company career page 12 hours ago
Skills & Technologies
AI in the day-to-day
Engineers work on advancing models' capabilities for computer use and safety.
Requirements
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Not disclosed in this posting: years of experience.
Benefits
Joblaze summary
In the role of Research Engineer on the Computer Use team at Anthropic, the individual will focus on enhancing AI models' capabilities to interact with and understand software interfaces. Key skills include proficiency in Python, experience with machine learning model training, and a strong collaborative approach. This position is ideal for someone with a background in software engineering and a passion for both research and product development, particularly in the context of AI safety and societal impact.
Joblaze insights
- Listed about 3 months ago — first seen on Joblaze July 1, 2026. Last confirmed on Anthropic's careers page October 9, 2026.
- Salary band is above the typical range for AI/ML roles (median ~$190,000).
- Starts above 99% of 113 comparable mid ai/ml roles in United States that list Python we track (median $150,000 across 49 companies). See Python salary trends
- Python appears in 48.1% of 466 comparable mid ai/ml roles in United States; reinforcement learning appears in 4.3% of 466 comparable mid ai/ml roles in United States.
Quick facts
- Is the Research Engineer, Computer Use role remote?
- It's hybrid — Anthropic expects some on-site time in San Francisco, CA | New York City, NY | Seattle, WA.
- What's the salary range?
- Anthropic lists $500,000–$850,000 for this role.
- Where is the role based?
- Anthropic is hiring for this position in San Francisco, CA | New York City, NY | Seattle, WA.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Machine Learning, Python, reinforcement learning.
- Does Anthropic sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- What seniority level is this role?
- Anthropic targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Research Engineer, Computer Use role at Anthropic.
From the original posting
About Anthropic
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.
Logistics
Standard company text repeated across Anthropic's postings is omitted here.