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Infrastructure Software Engineer
2 months ago
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 building the Waymo Driver-The World's Most Experienced DriverTM-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.
Job SummaryWe are seeking an experienced Infrastructure Software Engineer to join our Planner Infrastructure team. As a key member of our team, you will be responsible for designing and implementing software that runs on the self-driving car, as well as tools and benchmarking for ensuring that our system is reliable. You will work closely with our Technical Lead Manager to lead and help us take our system to the next level.
Key Responsibilities- Software Architecture and Implementation: Ensure that our software is architected for reliability and implemented using advanced technologies and engineering best practices.
- Software Testing and Validation: Conduct software testing and validation, including the use of simulation and static analyzers to ensure that there are no reliability problems in our software that runs on the road.
- System Performance Optimization: Ensure that our system can produce safe driving plans in an allotted timing and compute budget (potentially for hundreds of people and cars around the self-driving car).
- Real-time Hazard Detection and Response: Be able to react and change direction at super-human latencies when there are new hazards detected by our perception system.
- Machine Learning Model Performance: Ensure our machine learning models are performing well on GPU/TPU and other hardware accelerators.
- Education: BS in Computer Science, Electrical Engineering, Robotics, Physics, Math, or related field (or equivalent experience).
- Experience: 5+ years of industry experience designing and writing production code, 5+ years of experience in C++, Java, Rust, or other modern languages, and 5+ years of experience leading technical contributions and excellent engineering execution.
- Experience with FAANG-scale infra platforms.
- Experience building performant and easy to use scalable systems and tools.
- Experience with ML model inference performance and frameworks like CUDA and JAX.
- Experience designing or writing software for high-reliability systems, performance optimization, or productionizing deep learning models on GPU for low inference latency.
