Machine Learning Engineer - ML Agents and Planning

About the role

The Offline Driving Intelligence team develops Foundation Models for ML Agents and applies them off-vehicle to provide generalization capabilities to simulation and validation. This team collaborates closely with the Planner, Simulation and Validation teams to develop and validate driving performance.

Responsibilities

• Develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like agents.
• Work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort, and realism.
• Contribute to our large-scale machine learning infrastructure to discover new solutions and push the 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.

Requirements

• PhD degree in computer science or related field or master's degree and 5+ years of professional experience in a relevant field.
• Experience in Planning and / or Prediction using Reinforcement Learning techniques.
• Experience with training and deploying transformer-based model architectures.
• Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines.
• Fluency in Python with a basic understanding of C++.

Qualifications

• Top tier publications (NeurIPS, ICML, CVPR)

Skills

• Experience with AI tools and technologies

Benefits

• Salary
• Amazon Restricted Stock Units (RSUs)
• Zoox Stock Appreciation Rights

Pay

$189,000 - $270,000 a year

Schedule

Full-time