Cerebras

FPGA Engineer

Sunnyvale, CA, Remote. Posted 3 months ago

The role

You will own the in-chassis IO subsystem, including RoCE v2 network interfaces, a programmable switching fabric, and Serial IO communication. You will develop solutions to optimize bandwidth and latency while interfacing with AI application, cluster architecture, and embedded software teams.

What you will do

  • Lead full chassis-to-wafer IO architecture and design
  • Improve current RTL, implement next-gen FPGA design, and define future IO architectures
  • Produce production-ready bitstreams for deployment into large clusters
  • Work with DV team to prevent bug slips and simplify debug
  • Optimize bandwidth/latency over FPGA datapath and all IO interfaces
  • Interface with board team facilitating and executing board bringup
  • Drive network performance debug of large AI clusters
  • Integrate leading edge networking technologies and protocols
  • Lead cross-functional technical projects spanning multiple teams
  • Foster clear and effective communication across teams and stakeholders

Required qualifications

  • 5+ years industry experience generating production FPGA solutions, OR Master's/PhD in Computer or Electrical Engineering + 3 years industry experience
  • Proficiency in Verilog development in Git based repo
  • Highly productive with FPGA placement & routing, timing closure, simulation, debug, and other FPGA tools/workflows
  • Network protocol familiarity (TCP, RoCE)
  • Network debug tools such as Wireshark

Nice to have

  • Knowledge of network switch environments (Arista, Juniper, etc.)
  • AI-augmented development environment

Benefits

  • Build a breakthrough AI platform beyond the constraints of the GPU
  • Publish and open source cutting-edge AI research
  • Work on one of the fastest AI supercomputers in the world
  • Job stability with startup vitality
  • Simple, non-corporate work culture that respects individual beliefs

About the company

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. The company works with leading model labs, global enterprises, and cutting-edge AI-native startups.