Software Engineer, GPU
Waymo - New York City, NY
posted 19 days ago
About the position
Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states. 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.
Responsibilities
- Collaborate with application teams to understand how to map newly developed 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
Requirements
- 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
Nice-to-haves
- 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
Benefits
- Discretionary annual bonus program
- Equity incentive plan
- Generous Company benefits program
