Research Engineer, Performance RL (Reinforcement Learning)

Anthropic; California (MO); Hybrid; USD 350,000 - 850,000; Full time

Job summary

Anthropic is seeking a Research Engineer for the Code RL team to advance models' ability to safely write correct, fast code for accelerators. You will design RL environments and evaluations, run experiments, and integrate results into training runs.

You will collaborate with researchers, engineers, and performance specialists across Anthropic. Applicants should have accelerator experience (CUDA, ROCm, Triton, Pallas) and ML frameworks (JAX, PyTorch), with work across kernels, model code, and

Qualifications

• Minimum education: Bachelor’s degree or equivalent.
• Experience with accelerators and ML frameworks (CUDA, ROCm, Triton, Pallas; JAX or PyTorch).
• Ability to design and implement RL environments and evaluations.
• Capability to balance research exploration with engineering implementation.

Responsibilities

• Invent, design and implement RL environments and evaluations.
• Conduct experiments and shape research roadmap.
• Deliver work into training runs.
• Collaborate with researchers, engineers, and performance specialists.

Skills

Accelerator expertise

CUDA

ROCm

Triton

Pallas

JAX

PyTorch

Distributed systems

Kernels

Model code

Education

Bachelor's degree

Tools

CUDA

ROCm

Triton

Pallas

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 RL Teams

• Developing systems that enable models to use computers effectively
• Advancing code generation through reinforcement learning
• Pioneering fundamental RL research for large language models
• Building scalable RL infrastructure and training methodologies
• Enhancing model reasoning capabilities

We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting‑edge research and engineering excellence, with a deep commitment to building high‑quality, scalable systems that push the boundaries of what AI can accomplish.

About the Role

We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to safely write correct, fast code for accelerators.

Specifically, you will:

• Invent, design and implement RL environments and evaluations.
• Conduct experiments and shape our research roadmap.
• Deliver your work into training runs.
• Collaborate with other researchers, engineers, and performance engineering specialists across and outside Anthropic.

You may be a good fit if you:

• Have expertise with accelerators (CUDA, ROCm, Triton, Pallas), ML framework programming (JAX or PyTorch).
• Have worked across the stack – kernels, model code, distributed systems.
• Know how to balance research exploration with engineering implementation.
• Are passionate about AI's potential and committed to developing safe and beneficial systems.

Strong candidates may also have:

• Experience with reinforcement learning.
• Experience porting ML workloads between different types of accelerators.
• Familiarity with LLM training methodologies.

Annual Salary

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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

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.

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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.