Zoox
Senior/Staff Software Engineer, ML Training Optimization
Foster City, CA · Staff+
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DOL prevailing wage, 2026-27 wage year · Data Scientists (15-2051) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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About the role
- You'll set technical direction for distributed training, parallelism strategies, mixed-precision training, and RL on SOTA accelerators, especially for multi-modal VLA and VLM models.
- 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.
Responsibilities
- Lead the design, implementation, and operation of training performance optimizations (data/tensor/pipeline parallelism, mixed precision, gradient checkpointing, GPU kernels) to scale VLM, VLA, and Foundation model training.
- Own the technical strategy and multi-quarter roadmap for RL framework and RL performance optimization for driving foundation models.
- Drive profiling and root-cause analysis of throughput bottlenecks across the compute, compiler, framework, and cluster-networking stack.
- Build custom kernels and benchmarks that track and validate performance gains across the stack.
- Mentor engineers and raise the team's technical bar through design reviews and best practices.
- Are you excited to own ML training optimization at Zoox and make the models that power autonomous driving train faster, cheaper, and at greater scale?
Requirements
- 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 (Megatron-LM, TorchTitan) and efficiently utilizing GPU/accelerator clusters at scale.
- Experience with RL frameworks (Verl/MILES) and algorithms (GRPO, PPO).
- Experience with collective communication libraries (e.g., NCCL) and optimizing communication/compute overlap in multi-node training.
- Proficiency in Python or C++.
- Experience with ML compilers, performance tooling, or hardware/software co-design (GPU/TPU/accelerator architectures).
- Ability to influence across teams and communicate technical tradeoffs to both researchers and engineers.
- About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market.
- Note: You do not have to meet all the requirements below to be considered for this position:
- Strong command of profiling tools (NVIDIA Nsight, PyTorch Profiler, or XLA/JAX profiling) to find and resolve training bottlenecks.
- About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn Accommodations If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter. A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
Compensation
- $254k-$350k
Company info
- We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
- Zoox is on a mission to reimagine transportation and build ground-up autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone.
- You'll partner with all Autonomy teams (Perception, Prediction, Planner, Simulation, Collision Avoidance) and act as a force multiplier for our internal customers, while mentoring engineers and shaping the team's roadmap as we expand into new ML domains.
This listing is sourced directly from Zoox's careers page and normalized into a canonical job model.