Zoox
Software Engineer, ML Training Optimization
Foster City, CA · Mid
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odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$29,565 more — $206,565 — moves this role to Level IV and 4 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $206,565 would place this position at wage Level IV. That figure is within the posted range, and I'd like to target it. This role classifies under "Data Scientists" for prevailing-wage purposes.
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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Green-card follow-through: 84%
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About the role
- 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.
Responsibilities
- Design, implement, and operate cutting-edge ML training performance optimization techniques - distributed training (data/tensor/pipeline parallelism), mixed-precision, gradient checkpointing, and GPU kernels - to scale our VLM, VLA, and Foundational models training efficiency.
- Are you excited to drive our ML Training Optimization initiatives and make the models that power autonomous driving trains faster, cheaper, and at greater scale?
- Collaborate closely with ML researchers, data engineers, and hardware engineers to define requirements and align on architectural decisions for large-scale training infrastructure.
- Implement custom kernels and build benchmarks to track and validate training-performance optimizations across the stack.
Requirements
- 4+ years of total experience, including 2+ years working on large-scale model training platforms.
- Experience with distributed training frameworks (Megatron-LM, TorchTitan), efficiently utilizing GPU/accelerator clusters at scale.
- Experience with RL framework such as Verl/MILES and RL algorithms(GRPO, PPO)
- Experience with collective communication libraries (e.g., NCCL) and optimizing communication/compute overlap in multi-node training.
- Experience using profiling tools (NVIDIA Nsight, PyTorch Profiler, or XLA/JAX profiling) to identify and resolve training bottlenecks.
- Experience with ML compilers, performance tooling, or hardware/software co-design (e.g., GPU/TPU/accelerator architectures).
- 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:
- Proficient in Python or C++.
- 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.
Skills
- Work on RL framework and RL performance optimization for driving foundation model
- Profile and debug training throughput bottlenecks across the compute, compiler, framework, and cluster-networking stack.
Compensation
- $177k-$270k
Company info
- 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.
- We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
This listing is sourced directly from Zoox's careers page and normalized into a canonical job model.