Zoox is looking for software engineers to help us build novel architectures for classifying and understanding the complex and dynamic environments in our cities. In this role, you will have access to the best sensor data in the world and an incredible infrastructure for testing, validating, and deploying your algorithms.
Our Prediction team’s role is to provide a probabilistic representation of the future state of the world; in particular, understanding what other vehicles, pedestrians, and cyclists will do next. We leverage both high quality sensor data and high level semantic information to produce data-driven models of the future. This representation is tightly integrated into our planning software to deliver a safe and smooth customer experience.
Qualifications
BS, MS, or PhD degree in computer science or related field
Fluency in C/C++
Experience with production ML pipelines: dataset creation, labeling, training, metrics
Experience with computer vision or machine learning techniques
Experience with autonomous robots/robotics
Bonus Qualifications
Extensive experience with programming and algorithm design
Ability to create functional real-time systems that solve difficult prediction tasks
Experience handling large data sets efficiently
Strong mathematical skills and understanding of probabilistic techniques
Experience with designing large scale scalable software architectures
Understanding of modern ML techniques
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.
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.
