About the Position

Research Engineer, RL Engineering

San Francisco, CA | New York City, NY | Seattle, WA

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 Role

Reinforcement learning (RL) is how Claude learns to reason, write code, and act autonomously over long horizons. This role sits on the team that builds and owns the RL training system: the system that trains our production models and that researchers across Anthropic run their experiments on. The team works closely with research teams across the company on the science and engineering of making RL work at scale.

As a Research Engineer on the team, you'll work at the center of RL at Anthropic. You'll have a direct view of how RL training behaves at the frontier because the system you own sits underneath both production and research runs. You will use it with collaborators across research teams to understand what is working, what is fragile, and where the next improvements are.

Key Responsibilities

Build, own, and improve the core RL training system that serves Anthropic's production and research runs
Work across the stack (orchestration, environments, training, inference, evaluation) wherever the system needs it
Study how RL training behaves at scale and contribute to the research that improves it, in collaboration with teams across Anthropic
Implement new training methods as stable, fast, well-tested code
Improve the speed and efficiency of RL training and evaluation through profiling, optimization, and benchmarking
Make the system easier for researchers to build on, through clean abstractions, clear APIs, and automated testing
Debug hard problems across the stack, from a run that has quietly drifted to a distributed systems failure that only shows up at scale
Communicate results clearly, in writing and in discussion

Minimum Qualifications

Proficiency in Python and experience working in, debugging, and improving a large ML codebase
Experience with large-scale machine learning training (reinforcement learning, pretraining, or post-training) or the systems that support it
Experience with at least one modern ML framework (JAX, PyTorch, or similar)
Ability to design controlled experiments and reach conclusions you and others can trust
Ability to balance research exploration with engineering implementation
Strong written and verbal communication skills
Care about the societal impacts of your work and are committed to developing safe and beneficial systems

Preferred Qualifications

Experience with reinforcement learning for large language models, in research, production, or both
Experience studying training at scale: scaling behavior, training dynamics, or method development on large models
Experience with large-scale distributed training systems
Familiarity with LLM architectures and training methodologies
Experience working close to a frontier training run
Experience profiling and optimizing the performance of ML workloads
Experience with RL environments, evaluations, or sandboxed code execution
Experience with Rust or C++
Enjoy pair programming (we love to pair!)

We Offer

Competitive salary range: $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.

About the Company

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

How We're Different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come Work with Us!

We believe that AI will have a transformative impact on the world, and we’re seeking exceptional candidates who collaborate thoughtfully with us to realize this vision. At the same time, we want to understand your unique skills, expertise, and perspective through our hiring process. We invite you to review our AI partnership guidelines for candidates and confirm your understanding by selecting “Yes.”

Apply for This Job

Please ensure to provide either your LinkedIn profile or Resume, we require at least one of the two.

Apply for this job

Research Engineer, RL Engineering

Job description