Research Engineer, Chip Design RL

Anthropic • San Francisco, CA

5h • Hybrid

About The Position

Anthropic is hiring a Research Engineer for the Code RL team within its Reinforcement Learning organization. The role advances models’ ability to design silicon by translating chip-design expertise into tasks and learning signals for models. The work includes creating RL environments and evaluations for agentic RTL generation, design verification (including formal verification), and physical-design optimization; addressing cross-cutting RL challenges such as EDA-tool latency optimization and proxy rewards; conducting experiments and shaping the team’s roadmap; delivering work into research and production training runs; and collaborating with researchers and engineers across and outside Anthropic.

Anthropic’s RL teams develop reinforcement-learning research and systems that contribute to its models, working across areas such as computer use, code generation, foundational RL research for language models, scalable training infrastructure, and model reasoning. The teams collaborate with alignment, frontier red-team, and applied production-training groups to bring research into deployed models while developing capable and safe systems.

The role requires expertise in ASIC or FPGA design, familiarity with industry EDA tools and processes, and experience taking chips from specification to silicon. A bachelor’s degree or an equivalent combination of education, training, and experience is the stated minimum. The position has an annual salary range of $500,000–$850,000. Anthropic currently expects staff to work from one of its offices at least 25% of the time, though some roles may require more. The company sponsors visas, subject to role and candidate circumstances.

Requirements

• Expertise in ASIC or FPGA design, including RTL, design verification (UVM, formal methods, or coverage-driven methods), physical design (synthesis, place-and-route, or timing closure), PPA optimization, DFT, or ECOs.
• Fluency with industry EDA tools and processes.
• Experience taking chips from specification to silicon, including having taped out chips.
• Ability to balance research exploration with engineering implementation.
• Passion for AI’s potential and commitment to developing safe and beneficial systems.
• Bachelor’s degree or an equivalent combination of education, training, and/or experience.
• A field of study relevant to the role, demonstrated through coursework, training, or professional experience.
• Years of experience required will correlate with the internal job-level requirements for the position.

Nice To Haves

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

Responsibilities

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

Benefits

• Competitive compensation and benefits.
• Optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours.
• Office space for collaborating with colleagues.
• Visa sponsorship, with reasonable efforts to secure a visa and access to immigration counsel.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level