Software Engineer, ML Performance Optimization
Zoox · On-site
MeritLog read this listing from Zoox's Lever job board and last checked it on September 9, 2026.
Source: the employer's Lever job board. Open the original listing for current details.
Job details
- Work model
- On-site
- Salary
- $177,000 - $270,000
- Location
- Foster City, CA
- Occupation
- Software Developers(O*NET 15-1252.00)
Hiring context
How this role compares at Zoox
Zoox has 245 live roles in MeritLog’s catalog across 11 job families, and 46 of them are in data & analytics. 231 of those listings publish a pay range, a disclosure rate of 94%.
This role's posted range of $177,000 - $270,000 sits above 50% of the 224 other Zoox roles quoted over the same currency and period.
Zoox concentrates this hiring in:
Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.
Job description
Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. The Opportunity Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent.