Research Engineer, Chip Design RL; Reinforcement Learning

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.

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 Fable 5 and Opus 4.8. 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  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.

We’re hiring for the Code RL team within the RL organization. As a Research Engineer, you’ll advance our models’ ability to design silicon. Hardware design is difficult and unforgiving – exactly the sort of domain we want Claude to excel at.

You'll leverage your chip design expertise and turn it into tasks and signals for models to learn from. Specifically, you will:

• Invent, design, and implement RL environments and evaluations for agentic RTL generation, design (including formal) verification, physical design optimization.
• Work on cross‑cutting RL considerations such as EDA‑tool latency optimization and proxy rewards.
• Conduct experiments and shape our roadmap.
• Deliver your work into research and production training runs.
• Collaborate with other researchers and engineers across and outside Anthropic.

• Have expertise in ASIC or FPGA design: RTL, design verification (UVM, formal methods, coverage‑driven), physical design (synthesis, place‑and‑route, timing closure), PPA optimization, DFT, ECOs.
• Are fluent with industry EDA tools and processes.
• Have taped out chips and have experience going from spec to silicon.
• Know how to balance research exploration with engineering implementation.
• Are passionate about AI’s potential and committed to developing safe and beneficial systems.

• Experience with reinforcement learning, evaluations or environments.
• Built tooling or automation around chip design flows.
• Worked on ML accelerators or high‑performance compute hardware.
• Familiarity with high‑level synthesis or architecture simulators.

Annual Salary:

$500,000—$850,000 USD

Minimum education: Bachelor’s degree or an equivalent combination of education, training, 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.

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.