Waymo-posted about 1 month ago
Full-time • Intern
Hybrid • Mountain View, CA
1,001-5,000 employees
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!

  • Design a hardware-friendly algorithm for compressing activations, weights and instructions in an ML accelerator
  • Develop a proof-of-concept hardware implementation of the compressor-decompressor
  • Study trade-offs between hardware complexity, performance, compression loss
  • Collaborate with ML model owners to estimate impact of compression on model quality
  • Enrolled in a Masters program in Electrical Engineering, Computer Engineering or equivalent
  • Strong understanding of computer architecture for domain-specific accelerators
  • Strong programming skills in C++ and/or Python
  • Proficiency in digital design using High-level synthesis, SystemVerilog or similar languages
  • Enrolled in a PhD program in Electrical Engineering, Computer Engineering or equivalent
  • Understanding of ML numerics, error analysis and model quality evaluations
  • Experience with domain-specific languages for hardware design (Eg. Chisel, Magma etc.)
  • Familiarity with high-level architectural simulators such as Gem5
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