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.
The Model Metrics and Introspection team is responsible for both (a) developing the capability to estimate the impact of model changes before they are shipped to production and (b) being able to root cause issues that arise during deployment. With increased reliance of ML models across critical on-vehicle and off-vehicle systems, the burden of validation also scales up, and this team’s role is to meet that challenge.
Responsibilities
- You work with your team to develop a large scale metric pipeline to characterize the impact of a new ML model on our driving software across Prediction and Planner. You will direct how the datasets are built and what metrics are to be computed to provide the most signal on potential impact during deployment.
- You will work closely with ML engineers to develop tools for analyzing errors and understanding the gaps in our systems and ultimately building a feedback loop from observing issues back to future model development.
- You will lead the team of engineers leveraging technical and managerial skills to deliver high-impact results.
- You will set the short and long term technical direction for the team and collaborate on the broader company-wide directions.
- You will grow the team through hiring and guide the continued professional development of team members.
- You will collaborate with engineers on Prediction & Behavior ML, Perception, Planner, Simulation, and Systems Design to solve the overall Autonomous Driving problem in complex urban environments.
Qualifications
- BS, MS, or PhD degree in computer science or related field
- Prior experience in managing engineers and building a team-Fluency in C++
- Extensive experience with programming and algorithm design
- Knowledge of distributed system design, implementation, and optimization
Bonus Qualifications
- Experience with production metrics pipelines
- Experience with the full life cycle of ML model development from training, metrics, putting into production, and analyzing errors
- Prior experience with autonomous vehicles 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.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.