# Research Engineer, Universes

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA, Seattle, WA, New York, NY
**Role:** AI Research
**Salary:** $500k – $850k/yr
**Skills:** Reinforcement Learning, LLMs, Simulation Systems, ML Infrastructure, Python, Distributed Systems, Containerization, Sandboxing, Virtual Machines, Software Engineering
**Posted:** 2026-02-12

> Builds next-generation training environments and evaluations for agentic AI models, blending research in reinforcement learning with robust engineering implementation. Requires strong technical judgment, agency, and experience in ML systems.

## Job Description

## About the Team

The Universes team within Research builds training environments for AI models to perform complex, long-horizon agentic tasks in ultra-realistic settings, teaching models to navigate ambiguity, handle interruptions, maintain context, and exercise judgment.

## About the Role

Research Engineers build next-generation training environments for capable and safe agentic AI. This role blends research and engineering, implementing novel approaches, contributing to research direction, reinforcement learning, environment design, and capability evaluations.

## Responsibilities

- Build the next generation of agentic environments
- Build rigorous evaluations that measure real capability
- Collaborate across research and infrastructure teams to ship environments into production training
- Debug and iterate rapidly across research and production ML stacks
- Contribute to research culture through technical discussions and collaborative problem-solving

## You may be a good fit if you

- Are highly impact-driven — you care about outcomes, not activity
- Operate with high agency
- Have good research taste or senior technical experience, demonstrating good judgment in identifying what actually matters in complex problem spaces
- Can balance research exploration with engineering implementation
- Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems
- Are comfortable with uncertainty and adapt quickly as the landscape shifts
- Have strong software engineering skills and can build robust infrastructure
- Enjoy pair programming (we love to pair!)

## Strong candidates may also have

- Industry experience with large language model training, fine-tuning or evaluation
- Industry experience building RL environments, simulation systems, or large-scale ML infrastructure
- Senior experience in a relevant technical field even if transitioning domains
- Deep expertise in sandboxing, containerization, VM infrastructure, or distributed systems
- Published influential work in relevant ML areas

## Logistics

**Education requirements:** At least a Bachelor's degree in a related field or equivalent experience.

**Location-based hybrid policy:** Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

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