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Job Description

The Behavior Capabilities opportunity falls within the Fail Operational Planning team at Zoox. This team works to ensure that the robot continues to operate effectively, even in the presence of minor compartmentalized failures or degraded capabilities. The focus of the team includes developing behavioral and motion planning algorithms to improve trip progress, vehicle uptime metrics, and correspondingly a better customer experience. This is a cutting-edge problem which requires teamwork and collaboration across a diverse group of experts including Planner, Perception, Prediction, Hardware, and more. 
 
On this team, you will contribute to the next generation of algorithmic advancements to expand our robot’s ability to drive in some of the most complex scenarios. We are looking for an engineer who is excited to understand the interdependencies within the driving stack and takes ownership of their projects and has a holistic product focused approach towards development.

Responsibilities

  • Create principled algorithmic improvements to specific areas of driving behavior and implement those changes in our code base.
  • Collaborate cross-functionally to develop strategies and intelligent behaviors to mitigate the performance degradation under various failure modes of the system.
  • Architect and implement scalable solutions ensuring seamless integration with the rest of the driving stack.
  • Partner with validation teams to define and execute tests for developed algorithms.

Qualifications

  • Master's degree in Computer Science or related field
  • Fluency in C++
  • Extensive experience with programming and algorithm design
  • Understanding of vehicle kinematics
  • 4+ years of experience in a related field

Bonus Qualifications

  • PhD in Computer Science, Electrical Engineering, Mechanical Engineering, or related field
  • Experience shipping products to market (commercial robotics, drones, consumer devices etc.)
  • Demonstrated ability to create real-time motion planning algorithms in a cross-functional team
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.
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Zoox
Robotics & Autonomy · 500+ Members · Foster City, CA, United States

Zoox, an Amazon subsidiary, develops an autonomous ride-hailing service and a purpose-built electric robotaxi. Rather than adapting a conventional car, it designed a bidirectional vehicle around autonomous operation, passenger use, and dense urban mobility. The company develops the vehicle, autonomous-driving software, sensing, simulation, fleet systems, and rider experience as one integrated service. Zoox is progressing from testing toward commercial robotaxi operations with safety and controlled deployment at the center of its approach.

All jobs at Zoox
Job Overview

Approx. salary range

205K – 338K

Our estimate — this employer did not publish a salary

Our estimate, not the employer’s. Worked out from the middle half of 25 comparable roles on Neural Jobs that did publish a salary, in the same field, country and experience band. The real figure for this job may be different.

Eligibility
United States Right to work in the United States required.
Workplace
Hybrid
Job Posted:
1 year ago
Job Type
Full Time
Education
Any
Experience
3-4 years

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