Zoox
Senior/Staff Software Engineer, ML Training Optimization
$254K–$350K
Foster City, CA +1 · On-site · Staff · Full-time · Posted Oct 16, 2026
- Location
- Foster City, CA
Seattle, WA - Experience
- 7+ years total, including 4+ years on large-scale model training platforms.
About the job
Leads optimization of large-scale ML training for autonomous-driving foundation, VLM, and VLA models, including distributed training and reinforcement learning.
What you'll do
- Design and operate training performance optimizations, including parallelism, mixed precision, gradient checkpointing, and GPU kernels.
- Set the technical strategy and roadmap for reinforcement-learning frameworks and performance optimization.
- Profile and resolve training bottlenecks; partner across teams, build benchmarks, and mentor engineers.
What they ask for
- 7+ years of total experience, including 4+ years on large-scale model training platforms, with a record of leading projects end to end.
- Deep experience with distributed training frameworks and using GPU/accelerator clusters at scale.
- Experience with RL frameworks and algorithms, collective communication libraries, and profiling tools.
- Proficiency in Python or C++; ability to influence across teams and communicate technical tradeoffs.
Nice to have
- Experience with ML compilers, performance tooling, or hardware/software co-design (GPU/TPU/accelerator architectures).
Pay
USD 254,000–350,000 (per-year-salary), base salary
Tools
Megatron-LM, TorchTitan, Verl/MILES, GRPO, PPO, NCCL, NVIDIA Nsight, PyTorch Profiler
AI focus
Optimize training for autonomous-driving foundation models, including VLMs and VLAs, and develop reinforcement-learning training performance.
Model-written summary · the original posting is authoritative