ML Accelerator Modeling Engineer (TW)

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.

In this hybrid role, you will report to a Hardware Engineering Manager

You will:

• Create architectural models for exploration, development and verification of machine learning accelerators
• Analyze workloads, define and derive representative microbenchmarks 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

You have:

• BS degree in Computer Science or Computer Engineering or equivalent, or equivalent practical experience
• 3+ 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

We prefer:

• 1+ years experience modeling machine learning architectures in C++ simulators
• 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
• Strong English communication skills (written and verbal)

#LI-Hybrid