The Perception Object Detection and Tracking team at Zoox deals with perception of all people and objects that have a capability to move. Your role is to work with the ML model teams to bring cutting-edge models into the vehicle stack.
In this role, you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms. We are creating new algorithms for segmentation, tracking, classification, and high-level scene understanding, and you could work on any (or all!) of these components.
In This Role, You will...
Work on implementation of core tracking results from the Perception stackWork with both the model teams and optimization teams to develop a highly performant and efficient system that can run on vehicle.Work with Perception data, both on the input and output of machine learned modelsTake tracking output and integrate this into the larger behavioral system in the Autonomy stack
Qualifications:
BS or higher in Computer Science or a related degreeFluency in C++ and PythonExperience delivering ML model integration in latency-sensitive systemsHave experience implementing tracking systemsStrong mathematical skills and understanding of probabilistic techniques
Bonus Qualifications:
Familiarity with modern, Sparse-BEV Joint Detection and Tracking modelsExperience with CUDA codeContribute to the ongoing development of new architecture based on new, state-of-the-art ML researchInvestigate, prototype and train / evaluate networks for solving causal / recursive multi-target multi-modal tracking problem