Code RL Research Engineer: AI Hardware & RTL Innovation

Anthropic

San Francisco (CA)

Híbrido

USD 500.000 - 850.000

Jornada completa

14 días+
Generador de candidaturas

Una candidatura hecha a medida para este puesto de trabajo — un currículum y una carta de presentación adaptados que responden directamente a la oferta.

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Ventajas ofrecidas por este puesto de trabajo

Flexible hours
Generous vacation
Parental leave
Equity donation matching
Supportive office environment

Descripción de la vacante

Anthropic's RL team is hiring a Research Engineer to advance silicon design for Claude models. You will design RL environments, perform RTL verification, and optimize physical design flows across ASIC/FPGA toolchains as part of a cross‑functional research and production loop.

Collaborate with researchers and engineers to ship scalable RL tools, contribute to ML accelerators and high‑performance compute hardware, and help shape the team's roadmap and impact.

Formación

  • Bachelor’s degree or equivalent combination of education, training, and/or experience.
  • Experience with RTL design verification and ASIC/FPGA flows is required.
  • Fluency with industry EDA tools and processes.

Responsabilidades

  • Invent, design, and implement RL environments and evaluations for agentic RTL generation 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 work into research and production training runs.
  • Collaborate with other researchers and engineers across and outside Anthropic.

Conocimientos

ASIC/FPGA design RTL
RTL verification
PPA optimization
DFT
ECOs

Educación

Bachelor’s degree or equivalent
Field relevant to role

Herramientas

EDA tools

Descripción del empleo

Anthropic's RL team is hiring a Research Engineer to advance silicon design for Claude models. You will design RL environments, perform RTL verification, and optimize physical design flows across ASIC/FPGA toolchains as part of a cross‑functional research and production loop.

Collaborate with researchers and engineers to ship scalable RL tools, contribute to ML accelerators and high‑performance compute hardware, and help shape the team's roadmap and impact.

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