Research Engineer, Universes Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, W[...]

Anthropic; San Francisco (CA); Remote; USD 500,000 - 850,000; Full time

Job summary

Anthropic is seeking a Research Engineer to build the next generation of training environments for safe and capable AI. This role blends research with engineering responsibilities, requiring you to implement novel approaches while contributing to research direction.

You will collaborate with teams to design evaluations and methodologies, debug various ML stacks, and participate in technical discussions.

Compensation ranges from $500,000 to $850,000 USD based on experience and expertise.

Qualifications

• Bachelor’s degree or equivalent experience required.
• Experience in reinforcement learning or ML infrastructure preferred.
• Strong software engineering skills needed.

Responsibilities

• Build the next generation of agentic environments.
• Collaborate across teams to ship environments into production.
• Debug and iterate across research and production ML stacks.

Skills

Impact-driven

Strong software engineering skills

Research taste and judgment

Ability to balance research and engineering

Comfort with uncertainty

Education

Bachelor’s degree or equivalent

Tools

Containerization

VM infrastructure

Job description

Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY

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

Compensation

$500,000 - $850,000 USD

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• 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.
• Visa sponsorship: We do sponsor visas. However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

Equal Employment Opportunity

As set forth in Anthropic’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.