Senior / Staff Machine Learning Engineer
Zoox
Senior / Staff Machine Learning Engineer
Zoox
Fully electric autonomous ride-hailing service platform
Salary Range: 254000 to 366000 (Currency: USD) (Pay period: per-year-salary)
Develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like driving agents.
Work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort and realism.
Build generative behavior models (e.g. autoregressive, diffusion) that are conditionable on scenario intent — "cut off the ego vehicle," "jaywalk here" — for targeted stress-testing.
Leverage our compute, infrastructure and large corpus of data to push boundaries of the field.
Develop metrics and tools to analyze errors and understand improvements of our systems.
Collaborate with engineers on Perception, Planning, Simulation, and Validation to solve the overall Autonomous Driving problem.
PhD degree in computer science or related field and 4+ years of relevant professional experience or master's degree and 7+ years of relevant professional experience
Experience in one of the following: Planning, Prediction, Reinforcement Learning, Imitation Learning, generative modeling (diffusion, autoregressive models)
Experience with training and deploying transformer-based model architectures
Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
Fluency in Python ML frameworks and a basic understanding of C++
Top tier publications (NeurIPS, ICML, CVPR)
Experience with JAX
Zoox designs and operates an autonomous ride-hailing service built around a purpose-built, fully electric vehicle designed specifically for autonomous operation. The vehicle uses advanced sensors, cameras, and AI to navigate complex urban environments, offering a four-passenger interior for comfort. Unlike competitors that retrofit existing cars, Zoox engineers both the vehicle and the service from the ground up, enabling optimized safety, efficiency, and passenger experience through integrated software that optimizes routing and reduces wait times. The company emphasizes safety through extensive testing and regulatory collaboration, and sustainability via electric mobility. The ultimate goal is to provide a smarter, safer, and more efficient urban transportation system that improves city life while reducing emissions.
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