Engineering Manager, Compute Optimization

Zoox•Foster City, CA

22h•$245,000 - $307,000

About The Position

Zoox is building the world's most advanced self-driving hardware and software solution. The efficiency demands of such a system require an expert fine tuning of both the compute hardware architecture as well as the algorithms and middleware that runs on it to achieve maximum throughput at the most optimal power levels. The Software Performance team keeps the PCU alive, healthy, and performant to ensure that our on-bot autonomy software meets its latency targets while also accommodating its safety goals. As a Compute Optimization team leader within the Software Core Performance team, you will lead a highly specialized team of software performance engineers in aggressively optimizing on-bot software runtime. This is a high impact role that sits at the intersection of ML Platform, Core, and Autonomy Software - ensuring that efficient compute utilization is a central tenet emphasized across the organization.

Requirements

BS in computer science, computer engineering, or related field
Proficiency with C++ & concurrent execution (parallel) programming frameworks
Deep knowledge and understanding of CPU and recent GPU microarchitectures (e.g. Ampere, Blackwell)
Proven track record of cross-functional collaboration and leadership alignment
Prior experience managing teams of three or more FTE software engineers

Nice To Haves

Experience in robotics, aviation, automotive, or high-performance computing space
Have shipped real-time or near-real-time software autonomy or robotics software in production
Experiencing debugging and optimizing CPU, GPU kernels, and ML models using tools like Nsight Systems and Compute, Perfetto or similar compute observability tools

Responsibilities

Manage a team of 4-6 engineers focused on optimizing the software performance of the on-bot autonomy software stack.
Lead cross-functional optimization efforts with the goal of hitting strict system response (latency) targets.
Achieve alignment between cross-functional leaders across the Software organization on compute resource allocations and budgets.
Hire, grow, and develop talent in the realm of performance optimization.
Build self-service frameworks that shifts performance optimization left to developers so that individual engineers can have quick iteration optimization loops.