Company Overview
Waymo is an autonomous driving technology company with the mission to be the most trusted driver. Since its inception as the Google Self-Driving Car Project in 2009, Waymo has focused on developing the Waymo Driver—The World's Most Experienced Driver™—to improve mobility access and enhance road safety.
The Waymo Driver powers:
- Waymo One, a fully autonomous ride-hailing service.
- Various vehicle platforms and product use cases.
With over one million rider-only trips completed, Waymo's autonomous system is backed by:
- Tens of millions of miles driven on public roads.
- Tens of billions of miles driven in simulation across 13+ U.S. states.
About the Compute Team
The Compute Team plays a crucial role in delivering the compute platform responsible for running Waymo’s fully autonomous vehicle software stack.
Our mission includes:
- Designing high-performance custom silicon.
- Developing cutting-edge system-level compute architectures.
- Optimizing performance, power, and latency.
- Enhancing both hardware and software through cross-functional collaboration.
In this hybrid role, you will report to a Senior Staff Engineer.
Responsibilities
- Collaborate with application teams to map algorithms to GPUs, enhancing vehicle perception, intelligence, and reaction speed.
- Develop primitives and abstractions to scale codebases for evolving workloads and hardware.
- Improve and extend compiler optimizations to generate optimized GPU assembly.
- Analyze performance counters, GPU micro-architecture, and algorithms to identify optimizations.
- Contribute to infrastructure for testing, static analysis, and automated alerts to enforce GPU performance best practices.
- Co-design hardware features and evaluate trade-offs for future compute platforms.
Minimum Qualifications
- 5+ years of C++ programming experience.
- Advanced degree in Computer Science or related technical field (or equivalent practical experience).
- 5+ years of experience with GPU programming/optimization using CUDA or similar technologies.
- 1+ years of experience with GPU architecture and programming models.
- 5+ years of experience with performance analysis tools and debuggers.
- 5+ years of experience with parallel computing/programming.
Preferred Qualifications
- Experience with LLVM, SPIR-V, or other compiler projects.
- Experience with operating systems or embedded software, especially device drivers.
- Expertise in GPU optimization techniques (e.g., memory coalescing, register/shared memory tiling, pinned memory, warp-level programming).
- Experience with GPU libraries (CUB, CUTLASS, Thrust, or Eigen).
- Research background in parallel algorithms, compilers, or computer architecture.
- Experience with graphics workloads and shader programming.
- Familiarity with ML frameworks, compilers, or libraries.
Compensation & Benefits
- Base Salary Range: $192,000—$243,000 USD (varies by location, experience, and qualifications).
- Additional Compensation & Benefits:
- Annual discretionary bonus program.
- Equity incentive plan.
- Comprehensive company benefits package.
💡 Your recruiter will provide specific salary details for your location during the hiring process.
#LI-Hybrid
