Description

The TeleGuidance Planning team at Zoox enables our autonomous vehicles to incorporate human contextual guidance into the planning algorithms, allowing our vehicles to successfully reason about and navigate complex scenarios by leveraging real-time remote human guidance. TeleGuidance is an integral part of the self-driving stack, dealing with some of the most challenging scenarios by fusing the “human sensor” data in real-time to plan a solution to complete the mission. 


Take a look at this video we made for a more thorough explanation: https://youtu.be/NKQHuutVx78


Zoox is looking for a collaborative planning software engineer to join our Planning and Control team. In this role, you will help us develop planner behavior and trajectories in collaboration with remote guidance and write on-vehicle C++ components that integrate human guidance into the execution of our robot. You’ll solve the most complex and challenging edge cases for autonomous systems that are absolutely crucial to enabling Zoox’s mission. 

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Responsibilities
  • You will write on-vehicle C++ code that seamlessly integrates guidance provided by remote operators into the autonomous planner stack.
  • Within the Planner organization, you will work with fellow engineers from vertical teams (agent handling, junctions, etc.), and you will represent TeleGuidance as a member on horizontal teams (construction zones, emergency vehicles, etc.).
  • You will design and implement new tools and features that remote operators will use to help our fleet of vehicles to navigate complex dense urban driving environments. You will work with QA to develop a test plan for your new features.
  • You will have the opportunity to contribute to a broad portion of the code base, as dictated by your skills and interests. Members of our team have contributed to motion planning, trajectory optimization, GPU code, offline tooling/simulation, cost tuning, and more.
  • You will collaborate with developers across the AI software organization as a whole: Prediction, Perception, Core/Infra, and more.


Qualifications
  • Master's degree in Computer Science or related field
  • Experience writing performance-critical production code in C++
  • Demonstrated ability to create real-time motion planning algorithms
  • Understanding of configuration spaces and a variety of planning techniques (A*, D*, RRTs, etc.)
  • Extensive experience with programming and algorithm design
  • Strong mathematical and geometrical skills
  • Experience leading small projects or teams


Bonus Qualifications
  • PhD in Computer Science or related field
  • Experience with autonomous robots, Telerobotics
  • Experience with CUDA, Protobuf, or TypeScript


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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.


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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.



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