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Onboard Software Performance Engineer (C++)
Waymo · Mountain View, CA · Posted 10 days ago
Shape the compute and latency budget of Waymo's self-driving stack, co-designing software with hardware to make the car run faster on every mile.
The Onboard Software Performance team ensures that systems running on our Waymo's meet strict performance requirements such as producing necessary outputs within strict latency targets and using the allocated amount of compute resources (CPU/GPU/TPU/RAM) for each respective submodule. All of this needs to be done at scale with performance guarantees of many 9s of reliability while promoting high velocity of system evolution.
- Develop ADV's modular architecture improvements and frameworks that maximize performance and compute use and ROI for driving quality
- Evolve our compute usage on the car and simulation to promote continued scaling where the system runs fast on the car and in our data center
- Collaborate with onboard teams to identify and improve compute performance bottlenecks across the stack to improve performance/driving quality
- Collaborate with hardware teams to codesign hardware/software and improve the software for best performance on our hardware platform
- Ensure reaction latency for collision avoidance with and help design novel system/architecture for extremely fast nominal performance
- Develop necessary high scale performance evaluation, debugging and software change management processes
- Improve system resource usage to simulation at scale in Cloud datacenters: minimizing CPU use and latency, minimizing RAM usage, intelligently determining which computations should happen on CPU, GPU, and TPU.
- BS in Comp Sci, EE, Robotics, Physics, Math, or related field (or equivalent experience)
- 3 years of experience as a software engineer or similar roles
- 3 years of experience in C++
- 3 year of experience optimizing software using profile guided techniques
- 2 years in infrastructure/systems/performance domain optimizing end-to-end systems
- 2 years of experience working on a large-scale/high complexity system (supported by hundreds of engineers)
- Experience in robotics
- Experience in low-level optimization techniques, frameworks (SIMD/CUDA) and ML performance/frameworks
- Experience in evaluation techniques
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