Research Engineer, Universes at Anthropic — Remote North America

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Team

The Universes team within Research is responsible for training AI models to perform complex, difficult, long-horizon agentic tasks in ultra-realistic settings. We design and implement novel training environments that go far beyond what models can do today — environments where models learn to navigate ambiguity, handle interruptions, maintain context over extended interactions, and exercise judgment in open-ended scenarios.

About the Role

We're looking for Research Engineers to help us build the next generation of training environments for capable and safe agentic AI.

This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to research direction. You'll work on fundamental research in reinforcement learning, designing training environments and methodologies that push the state of the art, and building evaluations that measure genuine capability.

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 one or more of the following:

Have industry experience with large language model training, fine-tuning or evaluation

Have 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

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.