Senior/Staff Software Engineer, Zoox

• BS, MS, or PhD degree in computer science or related field
• Experience with training and deploying transformer-based model architectures and reinforcement learning
• Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
• Fluency in C++ or Fluency in Python with a basic understanding of C++
• Extensive experience with programming and algorithm design
• Strong mathematics skills

Desirable

• The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation
• Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior
• We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance
• As a Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive
• Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior
• You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle
• You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc
• You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
• You will develop metrics and tools to analyze errors and understand improvements of our systems
• You will collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments