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.
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
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
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