Research Engineer, Universes

Menlo Ventures; San Francisco (CA); On-site; USD 500,000 - 850,000; Full time

Job summary

A leading AI research organization is seeking a Research Engineer to develop the next generation of training environments for safe agentic AI. This role requires strong software engineering skills and the ability to balance research and implementation while working collaboratively across teams. Candidates should have a Bachelor's degree in a related field and a passion for building beneficial AI systems. Compensation ranges from $500,000 to $850,000 USD, including equity and benefits.

Qualifications

• Experience with large language model training or evaluation.
• Competence in debugging ML stacks.
• Ability to handle uncertainty and adapt quickly.

Responsibilities

• Build the next generation of agentic environments.
• Collaborate across teams to integrate environments into production.
• Measure genuine capability through rigorous evaluations.

Skills

Strong software engineering skills

Research taste and technical experience

Ability to collaborate effectively

Impact-driven mindset

Education

Bachelor's degree in a related field

Tools

Reinforcement Learning

Large Language Models

Distributed systems

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 (includes equity, benefits, and OTE)

Logistics

Education: Bachelor's degree in a related field or equivalent experience.

Location-based hybrid policy: All staff are expected to be in an office at least 25% of the time. Roles may require more on-site work as needed.

Visa sponsorship: We sponsor visas and will make every reasonable effort to obtain a visa if an offer is made.

Equal Employment Opportunity

Anthropic is an equal opportunity employer. We do not discriminate on the basis of any protected group status under any applicable law. Anthropic is committed to a diverse workforce and encourages applicants from all backgrounds.