Zoox
Engineering Manager, ML Performance Optimization
$276K–$343K
Foster City, CA · Hybrid · Manager · Full-time · Posted Oct 6, 2026
- Experience
- 8+ years of relevant experience, including 3+ years of management experience managing engineers.
About the job
Leads ML performance engineering to optimize training and inference infrastructure and models for autonomous driving across vehicle and cloud systems.
What you'll do
- Set the strategy and roadmap for ML training and inference performance optimization.
- Lead development and operation of ML infrastructure and drive end-to-end training and inference optimization.
- Hire, mentor, and lead engineers while partnering with research, software, data, and hardware teams.
What they ask for
- 8+ years of relevant experience, including 3+ years of management experience managing engineers.
- Strong background in ML performance optimization, including distributed training, GPU and kernel optimization, model compression, and profiling.
- Experience building user-friendly ML infrastructure for large-scale training and high-throughput, low-latency serving.
- Experience with ML training frameworks and GPU-accelerated inference frameworks; proven cross-functional collaboration and delivery of measurable performance improvements.
Pay
USD 276,000–343,000 (per-year-salary); base salary
Tools
FSDP/ZeRO, CUDA, Triton, torch.compile, XLA, TVM, PyTorch, JAX
AI focus
Optimizes large-scale model training and inference, including distributed training, GPU utilization, compression, and low-latency on-vehicle inference for autonomous driving.
Model-written summary · the original posting is authoritative