Chip Design Research Engineer: RL for Silicon AI

Anthropic Limited; San Francisco (CA); On-site; USD 500,000 - 850,000; Full time

Benefits offered by this job

Visa sponsorship

Office in SF

Job summary

Anthropic Limited is looking for a Research Engineer to join the Code RL team. You will advance models' ability to design silicon, leveraging chip design expertise to create RL environments for RTL generation and verification.

The role blends research with engineering, delivering results into both research and production training runs. Key responsibilities include optimizing RTL verification and physical design, collaborating across teams, and contributing to scalable AI safety-focused hardware

Qualifications

• Bachelor’s degree in electrical engineering, computer engineering, or a related field.
• Experience with ASIC/FPGA design and RTL development.
• Proficiency with RTL design verification (UVM/formal methods).
• Experience taping out chips and going from spec to silicon.
• Strong balance of research and engineering implementation.

Responsibilities

• Invent, design, and implement RL environments and evaluations for RTL generation, design verification, and physical design optimization.
• Work on EDA-tool latency optimization and proxy rewards.
• Conduct experiments and shape the roadmap.
• Deliver work into research and production training runs.
• Collaborate with researchers and engineers across Anthropic.

Skills

RTL design

Verification

EDA tools

Chip fabrication

Education

Bachelor’s degree

Tools

UVM

Formal methods

Synthesis

Place-and-route

Timing closure

DFT

ECOs

Job description

Anthropic Limited is looking for a Research Engineer to join the Code RL team. You will advance models' ability to design silicon, leveraging chip design expertise to create RL environments for RTL generation and verification.

The role blends research with engineering, delivering results into both research and production training runs. Key responsibilities include optimizing RTL verification and physical design, collaborating across teams, and contributing to scalable AI safety-focused hardware