Senior ML Accelerator Modeling Engineer

Waymo • Mountain View, CA

69d • $170,000 - $216,000 • Hybrid

About The Position

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's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the fully autonomous vehicle's software stack. To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency; and we collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world's highest performance automotive compute platforms.

Requirements

• Bachelor's degree in Computer Science or Computer Engineering or equivalent, or equivalent practical experience
• 7+ years on modeling complex, high performance architectures in the industry for functionality and/or performance
• Experience with cycle-level simulation frameworks (SystemC, Gem5 or similar)
• Strong C++ programming skills and familiarity with software development methodologies
• Solid foundation in computer architecture and principles of digital logic design

Nice To Haves

• 2+ years experience modeling high performance architectures such as CPU, GPU, NPU etc.
• Track record of building tools used by software and hardware teams for performance understanding and/or debug
• Experience writing and debugging microbenchmarks for performance correlation and correctness
• Excellent communication and problem solving skills

Responsibilities

• Create architectural, micro-architectural models for exploration, development and verification of machine learning accelerators
• Analyze workloads, define and derive representative micro-benchmarks for functional & performance goals
• Drive equivalence between actual hardware and simulator implementations, both for correctness and performance correlation
• Build scalable tools for modeling, performance analysis and optimization
• Interact with cross-functional engineering teams to identify opportunities and requirements

Benefits

• Discretionary annual bonus program
• Equity incentive plan
• Generous Company benefits program

What This Job Offers

• Job Type: Full-time
• Industry: Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services
• Education Level: Bachelor's degree
• Number of Employees: 1,001-5,000 employees