Machine Learning Engineer - Behavior Models for Road Users

Job description

Job responsibilities

• 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.

Job requirements

• PhD degree in computer science or related field or master's degree and 3+ 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