Engineering Manager, ML Platform

Zoox is on a mission to reimagine transportation and build autonomous robotaxis from the ground up that are safe, reliable, clean, and enjoyable for everyone. With bidirectional driving capabilities and four-wheel steering, our vehicle allows us to maneuver through compact spaces and change directions without needing to reverse. We are still in the early stages of deploying our robotaxis, and it is a great time to join Zoox and have a significant impact on executing this mission. 
Our growing Software Infrastructure engineering leadership team is looking for a Senior Engineering Manager, ML Platform. The centralized ML Platform team at Zoox plays a crucial role in accelerating innovation across all our Autonomy and Data Science teams by enabling them to develop and deploy models on our robotaxi and cloud infrastructure.
 
The Opportunity
We are continuing to push the boundaries of our ML capabilities by scaling our Vision Language Models (VLMs), Vision Language Action Models (VLAs), and World models, as well as our RL infrastructure, among other things. You will work across all ML teams within Zoox: Perception, Prediction, Planner, Simulation, and Collision Avoidance, building a cutting-edge distributed GPU training platform and enabling SOTA inference optimization techniques such as quantization, distillation, compression, and pruning.
You will lead a team of strong software engineers and managers 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 ML Infrastructure, here is one of our past talks at re:Invent.

In this role, you will:

- Vision: Develop and execute a strategic vision and roadmap for ML Training and Inference Performance Optimization, ensuring scalability, reliability, and performance to support autonomous driving.

- Technical acumen: Lead the design, implementation, and operation of a robust and efficient ML platform to enable the training, validation, serving, optimization and monitoring of ML models.

- ML Performance Optimization: Drive end-to-end performance optimization for large-scale model training and inference, including distributed training efficiency, GPU utilization, memory and communication optimization, model compression (quantization, pruning, distillation), and low-latency on-vehicle inference that meets strict real-time and compute budgets.

- Hiring: Attract, hire, and inspire a diverse world-class engineering team, fostering a culture of innovation, collaboration, and excellence.

- Partnership: Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisions.

- Mentorship: Enable engineers on the team to grow their careers by providing the right opportunities and clear, timely feedback.

Qualifications

- 8+ years of relevant experience, including 3+ years of management experience managing engineers.

- Strong technical background in ML performance optimization, such as distributed training strategies (data, tensor, pipeline parallelism, FSDP/ZeRO), mixed-precision training, kernel-level optimization (CUDA, Triton), compiler stacks (torch.compile, XLA, TVM), quantization, and profiling/benchmarking across GPU and embedded accelerators.

- Experience building user-friendly ML Infrastructure that enabled large-scale model training and high-throughput, low-latency serving use cases.

- Experience with training frameworks like PyTorch, JAX, etc., leveraging GPUs for distributed model training.

- Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks.

- Proven track record of extensive cross-functional collaboration, partnering with research, product, hardware, and platform teams to align priorities, influence technical direction, and deliver measurable performance improvements across organizational boundaries.

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 [email protected] 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.

Base Salary Range
 
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
 
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.