Posted by employer 2 years ago
First seen on Joblaze 5 months ago
Last verified on the company career page 7 hours ago
Skills & Technologies
Requirements
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Not disclosed in this posting: years of experience.
Benefits
Joblaze insights
- Listed about 5 months ago — first seen on Joblaze April 14, 2026. Last confirmed on Anthropic's careers page September 24, 2026.
- Salary band is above the typical range for AI/ML roles (median ~$190,000).
- Starts above 99% of 76 comparable mid ai/ml roles in United States that list AI/ML we track (median $150,000 across 35 companies). See AI/ML salary trends
- AI/ML appears in 51.2% of 441 comparable mid ai/ml roles in United States; Large Language Models appears in 3.4% of 441 comparable mid ai/ml roles in United States.
Quick facts
- Is the Research Scientist, Multi-Agent 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: AI/ML, Large Language Models, Multi-Agent Systems, 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 Scientist, Multi-Agent role at Anthropic.
From the original posting
About Anthropic
About the role:
Multi-Agent systems are becoming an increasingly important part of how AI is deployed, whether via fast small-model subagents inside a product, or large groups of agents solving very large problems. Training Claude to be maximally effective and safe within large groups is a challenging new area of reinforcement learning, and represents a new axis for scaling test time compute.
We are looking for researchers who have experience training multi-agent systems at the largest scale and an appreciation for the incentives and mechanism design that come into play.
Responsibilities:
- Help create and optimize environments and data for model training that maximize Claude’s performance or ease of use on agentic tasks
- Ideate, develop, and compare the performance of different agent harness configurations (eg memory, context management, communication architectures for agents)
- Design and implement rigorous quantitative benchmarks for large scale agentic tasks
- Work with our product org to find solutions to our most vexing challenges in applying agents to our products
You may be a good fit if you:
- Have experience with large-scale RL on language models
- Have experience training multi-agent systems
- Enjoy going deeply into the roots of a problem and understanding its foundations, rather than its surface.
- Have good communication skills and an interest in working with other researchers on difficult tasks
- Have a passion for making powerful technology safe and societally beneficial
- Are excited for a mission-driven org with fast-paced, impactful work
Representative projects:
- Design and build reinforcement learning environments to train groups of Claudes how to solve problems together efficiently
- Design and build agent affordances that unlock new capabilities and scales of agents, while keeping the Bitter Lesson in mind
- Design and build a novel eval that measures how large teams of agents interact in groups to solve problems
The annual compensation range for this role is listed below.
Logistics
Standard company text repeated across Anthropic's postings is omitted here.