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 and play a critical role in advancing our AI systems. We have 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’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.

• Invent, design, and implement RL environments and evaluations for agentic RTL generation, design (including formal) verification, and 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.

• 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.
• Fluency with industry EDA tools and processes.
• Experience tapping out chips and going from spec to silicon.
• Ability to balance research exploration with engineering implementation.
• Passion for AI’s potential and commitment 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.

$500,000—$850,000 USD

Minimum Education: Bachelor’s degree or 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:

Minimum years of experience correlate with the internal job level requirements.
Location-based Hybrid Policy: All staff are expected to be in one of our offices at least 25% of the time. Some roles may require more time in our offices.
Visa Sponsorship: We sponsor visas when possible and make reasonable efforts to assist with visa acquisition if an offer is made.

Competitive compensation and benefits, including flexible working hours, generous vacation and parental leave, optional equity donation matching, and a supportive office environment.