Senior/Staff Machine Learning Engineer - Prediction & Behavior ML

Key Skills

AI Robotic systems, Algorithms, Behavioral science, C++, Deep Learning, Design, Machine learning techniques, Mathematics, Python Programming

Job Description

The Prediction & Behavior ML team is responsible for developing machine-learned models that understand the full scene around our vehicle and forecast the behavior for other agents, our own vehicle’s actions, and for offline applications. To solve these problems we develop deep learning algorithms that can learn behaviors from data and apply them on-vehicle to influence our vehicle’s driving behavior and offline to provide learned models to autonomy simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team necessarily works very closely with the Planner team in the advancement of our overall vehicle behavior. The Prediction & Behavior ML team also works closely with our Perception, Simulation, and Systems Engineering teams on many cross-team initiatives.

Responsibilities

• You will develop new algorithms to model the future behavior of all other agents in the world
• You will develop new algorithms to model the future behavior of our own vehicle’s future actions, both in predicting our driving trajectories and estimating their quality in relation to our goals of safety, progress, and comfort
• You will develop new algorithms to apply generative deep learning to simulation to improve the realism of our offline validation systems
• You will build the foundation models for the on-vehicle and offline applications
• You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
• You will engineer software that runs on-vehicle to efficiently execute our algorithms in real time
• 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

Qualifications

• BS, MS, or PhD degree in computer science or related field
• Experience with training and deploying Deep Learning models
• 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

Bonus Qualifications

• Conference or Journal publications in Machine Learning or Robotics related venues
• Prior experience with Prediction and/or autonomous vehicles or robotics in general

Compensation

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $221,000 to $319,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.

Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

About Zoox

Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.