Foster City, California, United States, Foster City, California, US
Experience & eligibility
Experience
8+ years of relevant experience, including 3+ years of management experience managing engineers.
Inside the role
Department
ML Performance Engineering Leadership
Hiring specifics1 detail
Industry
Autonomous Vehicle Technology
Role signal brief
The role, at a glance
Extracted from the source posting · 95% confidence
Zoox is hiring an Engineering Manager to lead its ML performance optimization team. The role involves driving performance optimization for autonomous vehicle models and managing a team of ML engineers. It is a hybrid position based in Foster City, CA, with a salary range of $276k - $343k.
Compensation
USD 276,000–343,000 / year
What you need
8+ years of relevant experience, including 3+ years of management experience managing engineers
Strong technical background in ML performance optimization
Experience building user-friendly ML Infrastructure
Experience with training frameworks like PyTorch, JAX
Experience with GPU-accelerated inference using TensorRT, Ray Serve
Proven track record of extensive cross-functional collaboration
What you will own
Develop and execute a strategic vision and roadmap for ML Training and Inference Performance Optimization
Lead the design, implementation, and operation of a robust and efficient ML platform
Drive end-to-end performance optimization for large-scale model training and inference
Attract, hire, and inspire a diverse world-class engineering team
Collaborate closely with cross-functional teams to define requirements and align on architectural decisions
Enable engineers on the team to grow their careers by providing the right opportunities and clear, timely feedback
Core skills
ML Performance OptimizationDistributed TrainingGPU InferenceTeam LeadershipPyTorchTensorRTCUDAModel Compression
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 at a critical inflection point as we scale our robotaxi deployment, and it is a great time to join Zoox and have a significant impact on executing our mission.
Our growing ML performance engineering leadership team is looking for an Engineering Manager, ML Performance Optimization. The centralized ML performance team at Zoox plays a crucial role in enabling innovations across all our ML research teams to develop and deploy models across our robotaxi and cloud infrastructure and to advance cutting-edge training and inference optimization techniques.
The Opportunity
We are working on many interesting challenges to enable rapid experimentation and scale our multi-modal Foundation models and RL infrastructure, and ensure these models run efficiently on our vehicles, meeting our latency targets. You will get to work across all ML teams within Zoox - Perception, Prediction, Planner, Simulation and our Advanced Hardware Engineering group, and have the opportunity to significantly push the boundaries of ML scaling and acceleration at Zoox.
You will lead a team of strong ML performance engineers and this team has many growth opportunities as we expand our geofences at U.S markets 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.
Additional
About ZooxZoox 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 AccommodationsIf 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.
