Software Engineer, GPU

Waymo's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the completely 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 with many other teammates to ensure we design and improve hardware and software for maximum performance.

In this hybrid role, you will report to a Senior Staff Engineer.

You will:

• Collaborate with application teams to understand how to map newly developed and algorithms to GPU, allowing our cars to "see" further, operate smarter, and react faster
• Build primitives and abstractions that allow for scaling our code-base to constantly evolving workloads and hardware
• Improve and add new compiler optimizations to promote producing optimized GPU assembly
• Analyze performance counters, GPU micro-architectural features, and algorithms to identify optimization opportunities
• Contribute to infrastructure that performs testing / static analysis to catch bugs early and create automated alerts to encourage following best GPU performance practices
• Co-design hardware features and evaluate trade-offs for future generations of our compute platform

You have:

• 5+ years experience C++ programming skills
• Advanced degree in Computer Science, similar technical field of study, or equivalent practical experience
• 5+ years experience with GPU programming / optimization using CUDA or similar technologies
• 1+ years experience with GPU architecture / programming model
• 5+ years experience using performance analysis tools and debuggers
• 5+ years experience with parallel computing/programming

We prefer:

• Experience with LLVM or SPIR-V open-source ecosystems or other compiler projects
• Operating systems or embedded software experience especially working on device drivers
• Experience with GPU optimization techniques: memory coalescing, register/shared memory tiling, pinned memory, and warp-level programming
• Experience with GPU libraries: CUB, CUTLASS, Thrust, or Eigen
• Research experience in parallel algorithms, compilers, or computer architecture
• Experience with graphics workloads and shader programming
• ML frameworks/compiler/library

#LI-Hybrid