10 months ago
Responsibilities
- Develop deep learning models using imitation learning and reinforcement learning to generate driving plans for human-like agents.
- Develop techniques to estimate driving-plan quality across safety, progress, comfort, and realism.
- Contribute to large-scale machine learning infrastructure.
- Develop metrics and tools for error analysis and understanding system improvements.
- Collaborate with Perception, Planning, Simulation, and Validation engineers on autonomous driving.
- Develop foundation models for machine learning agents and planning to support simulation and validation.
Requirements
- PhD in computer science or a related field plus one year of professional experience, or an MSc plus five years of professional experience in a relevant field.
- Experience with planning and/or prediction using reinforcement learning techniques.
- Experience training and deploying transformer-based model architectures.
- Experience with production machine learning pipelines, including dataset creation, training frameworks, and metrics pipelines.
- Fluency in Python and a basic understanding of C++.
- Top-tier publications in venues such as NeurIPS, ICML, or CVPR are a bonus qualification.
Categories
ML EngineeringRobotics
About Zoox
Zoox builds a fully autonomous, purpose-built electric vehicle and the end-to-end platform to operate it as an urban robotaxi service. The company designs the vehicle, self-driving software, and fleet operations in-house to offer mobility-as-a-service rather than selling cars. Founded in 2014 and headquartered in Foster City, California, Zoox is a subsidiary of Amazon.