Senior Compute Optimization Engineering Manager

Zoox; Foster City (CA); On-site; USD 245,000 - 307,000; Full time

Benefits offered by this job

RSUs and stock options

Sign-on bonus

Health insurance

Job summary

Zoox is seeking a Compute Optimization team leader to spearhead performance work on the on-bot autonomy software stack. You will guide a team of engineers, drive latency-focused optimization, and coordinate with software leaders to allocate compute resources.

You will hire and mentor talent, build self-service performance tools, and push optimization early in the development cycle to accelerate iteration while maintaining safety and reliability goals.

Qualifications

• BS in computer science, computer engineering, or related field.
• Proficiency with C++ and concurrent execution (parallel) programming frameworks.
• Deep knowledge 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.

Responsibilities

• Manage a team of 7-10 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 latency targets.
• Align cross-functional leaders on compute resource allocations and budgets.
• Hire, grow, and develop talent in performance optimization.
• Build self-service frameworks that shift performance optimization left to developers.

Skills

C++ & concurrent execution

Cross-functional collaboration

Leadership alignment

Team leadership (3+ engineers)

Performance optimization

Education

BS in computer science or computer engineering

Job description

Zoox is seeking a Compute Optimization team leader to spearhead performance work on the on-bot autonomy software stack. You will guide a team of engineers, drive latency-focused optimization, and coordinate with software leaders to allocate compute resources.

You will hire and mentor talent, build self-service performance tools, and push optimization early in the development cycle to accelerate iteration while maintaining safety and reliability goals.