Research Engineer, Chip Design — Reinforcement Learning

Job Title

Research Engineer, Chip Design — Reinforcement Learning

Role Summary

Join the Code RL team within Anthropic's Reinforcement Learning organization to improve models' ability to design silicon. The role focuses on converting chip-design expertise into tasks, environments, and signals that enable agentic models to generate and optimize RTL, verify designs, and improve physical implementation.

Experience Level

Mid-level. Specific years of experience are not listed and will correlate with internal job level requirements.

Responsibilities

Work at the intersection of chip design and reinforcement learning to create environments, evaluations, and tooling that enable models to design and optimize hardware.

• Invent, design, and implement RL environments and evaluation metrics for agentic RTL generation and design verification (including formal methods).
• Develop environments and rewards for physical design optimization (synthesis, place-and-route, timing closure, PPA).
• Optimize EDA-tool latency, build proxy rewards, and integrate tooling to enable scalable training runs.
• Run experiments, analyze results, and shape the research and engineering roadmap.
• Deliver research artifacts into production training pipelines and collaborate across research and engineering teams.
• Communicate findings clearly to cross-functional partners and iterate on evaluation design.

Requirements

Must-have technical skills and practical experience relevant to applying RL to chip design. Education items are summarized separately below.

• Expertise in ASIC or FPGA design (RTL, design verification, physical design, PPA optimization, DFT, ECOs).
• Fluency with industry EDA tools and typical chip design processes and flows.
• Proven experience shipping silicon (taped-out chips) and taking designs from spec to silicon.
• Ability to balance research exploration with engineering implementation and production constraints.
• Expected to be onsite at an Anthropic office at least 25% of the time (hybrid work arrangement).
• Visa sponsorship is possible; hiring decisions will consider candidate eligibility and role requirements.

Nice-to-have:

• Experience with reinforcement learning, RL environments, or evaluation design.
• Built automation or tooling around chip design flows or EDA integration.
• Experience with ML accelerators, architecture simulators, or high-level synthesis.

Education Requirements

Minimum: Bachelor's degree or an equivalent combination of education, training, and/or experience in a relevant field. Expected fields include electrical/computer engineering, computer science, physics, or other technical disciplines demonstrated via coursework, training, or professional experience.

About the Company

Company: Anthropic

Headquarters: San Francisco, CA, United States

Anthropic is an AI research and safety company developing reliable, interpretable, and steerable large language models (Claude) and related tools, focusing on alignment, reinforcement learning, and scalable infrastructure for safe AI deployment.