Engineering Manager, Performance Optimization
Zoox
Listing collected from Zoox's career site. NextChapter is independent of Zoox.
Foster City, CA · Posted April 17, 2026
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Where Foster City, CA ranks
Where Foster City, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for pay after cost of living$209k · of 100
- #1Best cities for pay after cost of living in the West Coast$209k · of 39
- #1Best cities for pay after cost of living in California$209k · of 32
- #1Best cities for director and executive jobs in the West Coast38% · of 71
- #1Best cities for data and analytics pay after cost of living$232k · of 28
- #1Best cities for technology pay after cost of living$209k · of 80
Rankings about engineering jobs
- Best cities for software and engineering jobs #1 San Francisco (3,412 openings)
- Best cities for engineering pay after cost of living #1 San Mateo ($216k)
- Most requested AI skills in engineering jobs #1 AI tools in daily work (6.1%)
- AI tools named most often in engineering jobs #1 Claude (1.7%)
- Employers with the most engineering jobs #1 Amazon (2,992 roles)
Pay compared with the market
This listing does not state pay. Across 338 open engineering manager listings that state pay, the middle half runs $150,500 to $250,000 and the median is $200,500.
Listed pay is what employers advertise, not what people are paid.
How AI is used in this kind of work
AI use among architectural and engineering managers is little observed so far. Measured exposure for architectural and engineering managers: 3% (little observed).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
About the job
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.