The Collision Avoidance System (CAS) is responsible for detecting and reacting to imminent collision situations in support of our vehicle’s overall safety goals. CAS Perception is responsible for processing raw sensor data from our vehicle’s world-class sensor suite using a combination of geometric, interpretable algorithms and deep learning to detect near-collisions with obstacles along our intended driving path, in the most challenging dense urban environments and under tight compute resource constraints. Overall, CAS is parallel and complementary to our Main AI autonomy stack, and has a close relationship with our vehicle hardware and safety teams in order to architect redundancy into our overall driving system.

Responsibilities

  • You will lead a team of deep learning 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 coordinate cross-functional initiatives with other teams across CAS, Systems Engineering, QA, and more
  • You will develop new algorithms that consume raw sensor data input to detect dynamic entities in the world
  • You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
  • You will engineer software that runs on-vehicle to efficiently execute our algorithms in real time
  • You will develop metrics and tools to analyze errors and understand improvements of our systems
  • You will collaborate with engineers on the other parts of CAS Perception, CAS Verification & Validation, CAS Planner, and the Main AI teams to solve the overall Autonomous Driving problem in complex urban environments

Qualifications

  • BS, MS, or PhD degree in computer science or related field
  • Experience with training and deploying Deep Learning models
  • Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
  • Fluency in C++
  • Extensive experience with programming and algorithm design
  • Strong mathematics skills

Bonus Qualifications

  • Conference or Journal publications in Machine Learning or Robotics related venues
  • Prior experience with Prediction and/or autonomous vehicles in general
  • Fluency in Python
Vaccine Mandate

Employees working in this position will be required to have received a single dose of the J&J/Janssen COVID-19 vaccine OR have completed the two-dose Pfizer or Moderna vaccine series. In addition, employees will be required to receive a COVID-19 booster vaccine within two months of becoming eligible for the booster vaccine.

Employees will be required to show proof of vaccination status upon receipt of a conditional offer of employment. That offer of employment will be conditioned upon, among other things, an Applicant’s ability to show proof of vaccination status. Please note the Company provides reasonable accommodations in accordance with applicable state, federal, and local laws.

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.