The Prediction team is responsible for forecasting the future state of all the dynamic agents around our vehicle. To account for the inherent uncertainty of predicting the future, our job is to compute a probabilistic representation over the future intentions and movement of other agents. The output from our Prediction system is then tightly integrated into our Planning system to deliver a safe and comfortable ride.


  • Apply distributed compute algorithms to efficiently analyze petabytes of urban driving data
  • Work closely with ML engineers to develop metrics and tools for analyzing errors and understanding improvements in our systems
  • Engineer software that runs on-vehicle to efficiently execute our algorithms in real time
  • Collaborate with engineers on Perception and Planning to solve the overall Autonomous Driving problem in complex urban environments


  • BS, MS, or PhD degree in computer science or related field
  • Fluency in C++
  • Extensive experience with programming and algorithm design

Bonus Qualifications

  • Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
  • Experience with latency of analysis and optimization of safety critical software systems
  • Experience with petabyte-scale distributed computing (Spark, Databricks, generic MapReduce pipelines)
  • Prior experience with Prediction and/or autonomous vehicles in general
  • Strong mathematics skills
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.