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Manager, Prediction Integration

Zoox

Zoox

Foster City, CA, USA
Posted on Wednesday, July 19, 2023
The Active Prediction Integration team focuses on the integration of prediction and planning to achieve safe and high-performance autonomous driving. The team is responsible for one of the core algorithmic components of the AI stack that combines basic logic/physics models with advanced uncertainty-aware ML prediction models to reason about how the world evolves in response to candidate robot motions.
We are looking for a manager with a strong background in uncertainty-aware motion prediction and planning, and experience with both machine-learned as well as first-principles (e.g. physics-based) motion and logical reasoning models. The candidate will be responsible for working with the team to set the technical direction, evolve the current architecture and break new ground in further unification of planning, prediction, and perception.
The team collaborates closely with multiple groups across Planner and Zoox including ML behavioral modeling, search/optimization, cost design, prediction and perception. As a leader of the Active Prediction Integration team, the candidate will interact and coordinate efforts across multiple such teams and play a critical role in the evolution of the AI stack at Zoox. If you are passionate about working on fundamental robotic decision-making architectures and their deployment on a novel robot platform, we would like to hear from you.

In this role, you wlil:

  • Lead the design and development of integrated prediction and planning architectures
  • Set the short and long-term technical direction for the team and collaborate on broader, company-wide directions
  • Collaborate with the team members in technical design considerations, implementation, and on-vehicle testing
  • Coordinate cross-functional initiatives with other teams across Planning, Prediction, and Perception
  • Grow the team by partnering with recruiting and guide the continued professional development of team members

Qualifications

  • Extensive experience with AI and/or Robotics
  • Experience with current ML architectures and methodologies
  • Excellent communication and problem-solving skills
  • Experience with managing highly-technical teams of 5+ engineers
  • Relevant experience in the area of autonomous driving with a track record of delivering results in a production environment
  • MS or PhD in Computer Science (or a related field)

Bonus Qualifications

  • Experience with GPU/CUDA C++ architectures and algorithms
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 $220,000 to $330,000. 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.
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
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.