The Planner Interactions team is responsible for developing driving behaviors of the mobile robot, balancing safety, comfort, and progress. Planner Interactions emphasizes computationally efficient, simple, principled, and scalable approaches. The team handles their interactions with each other and other parts of the autonomy stack. We are looking for an experienced manager who is passionate about the exciting challenges involved in motion planning and decision making.
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
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.
In this role, you will:
You will lead the team of engineers on Planner Interactions, 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 collaborate with the team members in technical design considerations, implementation, and on-vehicle testing
You will coordinate cross-functional initiatives with other teams across Motion Planning, Prediction, Perception, and CAS
You will grow the team through hiring and guide the continued professional development of team members
Qualifications
Master’s or PhD in computer science, robotics, or a related field
7+ years of hands-on experience developing complex robotic systems or relevant software
Fluency in C / C++
Excellent communication and problem-solving skills
Prior engineering management experience with complex robotic systems
Extensive experience architecting and implementing motion planning algorithms
Bonus Qualifications
Experience with autonomous vehicles
Experience with reinforcement learning on physical systems
Familiarity in all or some of: trajectory optimization, search-based planning, Integration of prediction and planning, costs, risk assessment, multi-objective formulations
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