Posted 4 weeks ago Engineering Manager (ML Performance Optimization) Zoox› ★ 3.5 (375) Foster City, CA, United States 🇺🇸 Work arrangement not specified Full Time $276,000 - $343,000 year Apply on source site Track Check your resume for this jobPro Our growing ML performance engineering leadership team is looking for an Engineering Manager, ML Performance OptimizationThe 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 techniquesWe 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 targetsYou 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 ZooxYou 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 domainsVision: Develop and execute a strategic vision and roadmap for ML Training and Inference Performance Optimization, ensuring scalability, reliability, and performance to support autonomous drivingTechnical 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 modelsML 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 budgetsHiring: Attract, hire, and inspire a diverse world-class engineering team, fostering a culture of innovation, collaboration, and excellencePartnership: Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisionsMentorship: Enable engineers on the team to grow their careers by providing the right opportunities and clear, timely feedbackBenefitsPaid parental leaveAffinity groups and sports clubsWork from home opportunitiesHealth insuranceOur crew’s health and happiness is our first priority. We offer comprehensive health and mental health support, a wellbeing program, and unlimited and flexible paid time awayWe invest in our crew—and their families—for the long term. That includes generous family planning support, caregiver support, and strong cash compensation with great equity upsideWe look after our crew when they’re in the office too. Our famous food program is a great example, featuring a daily changing menu of local and sustainable dishesThere’s a busy calendar of social events at Zoox, with more sports teams than you can count. And, of course, playing with robots is an important part of the job descriptionExperience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworksStrong 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 acceleratorsExperience building user-friendly ML Infrastructure that enabled large-scale model training and high-throughput, low-latency serving use casesProven 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 boundariesExperience with training frameworks like PyTorch, JAX, etc., leveraging GPUs for distributed model training8+ years of relevant experience, including 3+ years of management experience managing engineersYou 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
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