Engineering Manager, Onboard Execution Performance

About The Role

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 main onboard computer healthy and performant to ensure that our on-bot autonomy software meets its latency targets while also accommodating its safety goals. We are responsible for the efficient allocation of onboard compute resources (CPU/GPU/Memory/accelerators) ensuring contention is minimized and the autonomy stack executes harmoniously.

As the Onboard Execution team leader within the 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.

In This Role, You Will:

• Manage a team of 8-to-10 engineers focused on optimizing the software performance of the on-bot autonomy software stack.

• Partner with Autonomy, ML Platform, Middleware, Sensors, and Hardware Architecture teams to meet strict system response (latency) and compute utilization 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 force-multiplier frameworks & workflows that empower developers to deliver efficient & performant software.

Qualifications And Requirements

• BS in computer science, computer engineering, or related field

• Proficiency with C++ & concurrent (parallel) execution systems

• Deep knowledge and understanding of the Linux operating system and GPU accelerated execution

• Proven track record of cross-functional collaboration and leadership alignment

• Prior experience managing teams of five or more full-time software engineers

Bonus Qualifications

• Hands-on experience with GPU runtime frameworks (CUDA, TensorRT, or XLA)

• 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 NVIDIA Nsight Systems and

• Compute, Perfetto or similar compute observability tools

Additional information

About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

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Accommodations If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.

A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

• BS in computer science, computer engineering, or related field

• Proficiency with C++ & concurrent (parallel) execution systems

• Deep knowledge and understanding of the Linux operating system and GPU accelerated execution

• Proven track record of cross-functional collaboration and leadership alignment

• Prior experience managing teams of five or more full-time software engineers

• Hands-on experience with GPU runtime frameworks (CUDA, TensorRT, or XLA)

• 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 NVIDIA Nsight Systems and

• Compute, Perfetto or similar compute observability tools

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