Software Engineer optimizing GPU-based algorithms for self-driving technology at Zoox. Analyzing performance and driving design decisions for advanced self-driving hardware and software solutions.
Responsibilities
Build real-time instrumentation for performance monitoring (CPU, GPU, latency, memory) and develop offline benchmarking frameworks, tools, and scripts to evaluate & analyze performance at scale in CI/vehicle, and establish budgets for next-gen architectures.
Analyze performance metrics to identify GPU hotspots and root causes, and propose and co-implement actionable solutions with component teams.
Support teams on bringing serial algorithms to the GPU to maximize compute utilization and improve overall latency.
Work as part of the Core team to design a middleware framework that promotes by default efficient and performant code development by maximizing CPU and GPU.
Requirements
BS in computer science or related field and 3+ years of experience.
Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and experience debugging/optimizing GPU kernels using tools like Nsight.
Strong knowledge of C++ and experience in large code bases, comfortable in Linux development environments.
Experience in development, debugging, and profiling of complex multiprocess systems (e.g., robotic systems, game engines).
Benefits
Health insurance
Long-term care insurance
Long-term and short-term disability insurance
Life insurance
Paid time off (e.g. sick leave, vacation, bereavement)
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