Staff Research Engineer, Discovery Team

Anthropic; San Francisco (CA); Hybrid; USD 350,000 - 850,000; Full time

Job summary

Anthropic is seeking a Research Engineer in San Francisco, CA to identify and resolve key challenges in developing scientific AGI. Ideal candidates will have over 8 years of ML research experience, proficiency in language model training, and a collaborative approach to problem-solving. Responsibilities include creating benchmarks for model capabilities and implementing distributed training systems. The position offers an annual salary ranging from $350,000 to $850,000. The role has a hybrid location-based policy requiring staff presence in the office at least 25% of the time.

Qualifications

• 8+ years of ML research experience.
• Familiarity with large scale language model training, evaluation, and inference.
• Expertise in performance optimization and distributed computing systems.

Responsibilities

• Identify and remove bottlenecks towards scientific AGI.
• Develop approaches for long-horizon task completion and reasoning challenges.
• Create benchmarks for evaluating model capabilities.

Skills

ML research

Language model training

Performance optimization

Distributed computing systems

Problem-solving

Education

Bachelor’s degree or equivalent

Tools

Docker

Kubernetes

Job description

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

Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. Our team likes to think across the whole model stack. Currently the team is focused on improving models' abilities to use computers – as a laboratory for long horizon tasks and a key blocker to many scientific workflows.

About The Role

As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimization, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged.

Responsibilities

• Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI
• Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery
• Scaling research ideas from prototype to production
• Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use
• Implement distributed training systems and performance optimizations to support large-scale model development

You May Be a Good Fit If You

• Have 8+ years of ML research experience
• Are familiar with large scale language model training, evaluation, and inference pipelines
• Enjoy obsessively iterating on immediate blockers towards longterm goals
• Thrive working collaboratively to solve problems
• Have expertise in performance optimization and distributed computing systems
• Show strong problem-solving skills and ability to identify technical bottlenecks in complex systems
• Can translate research concepts into scalable engineering solutions
• Have a track record of shipping ML systems that tackle challenging multi-step reasoning problems

Strong Candidates May Also Have

• Expertise with performance optimization for language model inference and training
• Experience with computer use automation and agentic AI systems
• A history working on reinforcement learning approaches for complex task completion
• Knowledge of containerization technologies (Docker, Kubernetes) and cloud deployment at scale
• Demonstrated ability to work across multiple domains (language modeling, systems engineering, scientific computing)
• Have experience with VM/sandboxing/container deployment and large-scale data processing
• Experience working with large scale data problem solving and infrastructure
• Published research or practical experience in scientific AI applications or long-horizon reasoning

Annual Salary

$350,000 - $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.