Research Engineer, Performance RL

Details

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

Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.6 and Opus 4.6. Our work spans several key areas:

• 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.

Role description

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. You'll need to know accelerator performance well to turn it into tasks and signals models can learn from.

Responsibilities

• 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.

Requirements / Qualifications

• Expertise with accelerators (CUDA, ROCm, Triton, Pallas) and ML framework programming (JAX or PyTorch).
• Experience working across the stack – kernels, model code, distributed systems.
• Ability to balance research exploration with engineering implementation.
• At least a Bachelor's degree in a related field or equivalent experience (education requirement).
• 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.

Compensation

Annual Salary:

$350,000 - $850,000 USD

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Logistics

• Location: San Francisco, CA
• 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. 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.

Benefits

Anthropic offers 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. 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 and are an extremely collaborative group that hosts frequent research discussions to ensure we are pursuing the highest-impact work.

How to apply

Applicants apply via the Anthropic careers page; the posting includes an application form and optional fields for preferences, visa/relocation questions, and voluntary self-identification surveys.