Software Engineer, ML Accelerator Modeling (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 onsite role, you will report to a Hardware Engineering Manager

You will:

• Prototype the hardware: Design and implement high-performance, high-fidelity C++ software models that serve as the blueprint for next-generation machine learning accelerators.
• Empower engineering velocity: Develop scalable software infrastructure and tools that enable the entire team to analyze performance data and rapidly optimize future hardware designs.
• Push the limits of silicon: Define and write rigorous software benchmarks to expose architectural bottlenecks, ensuring our hardware meets aggressive functional and performance goals.
• Verify correctness: Write critical validation code to guarantee that our software simulators serve as a "source of truth," accurately reflecting the behavior of complex hardware.
• Bridge the Hardware/Software gap: Collaborate closely with cross-functional engineering teams to drive requirements and gain deep expertise in the intricacies of ML accelerator architecture.

You have:

• BS degree in Computer Science or Computer Engineering or equivalent, or equivalent practical experience
• 2+ years of industry experience building performance-critical applications in C++
• Strong programming fundamentals - data structures, algorithms and problem solving ability
• Basic understanding of how programs execute on hardware and how to optimize performance

We prefer:

• Demonstrated ability to dive into new problem domains and apply your programming skills to solve them.
• Familiarity with fundamentals of computer architecture
• Experience with low-level systems programming, embedded systems, or performance optimization
• Prior experience in hardware or ML is a plus, but not required