Our Perception team is responsible for using our sensor data to understand the complex and dynamic environments where we drive. 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.
As a Senior Staff ML Engineer, you will lead the development of machine learning algorithms that can range in influence from onboard autonomy to offboard autonomy and validation. You will collaborate closely with other teams specializing in Prediction, Planning, Simulation, and Safety Validation, influencing our overall technical stack. Your role will look at problems in a way that crosses team boundaries to prototype new approaches that influence the long term technical direction of multiple organizations within the company. The impact of the role can be in the form of impacting immediate company milestones to leading forward-looking exploratory projects.
Responsibilities
Develop new algorithms to understand the scene around the robot, and how that scene would evolve through time
Build multi-modal foundation models for on-vehicle and offline applications
Develop new algorithms to apply generative AI to simulation to improve the realism of our offline validation systems
Leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
Provide technical mentorship to the broader group of ML developers at Zoox
Collaborate with engineers on Prediction, Planning, and Simulation 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 on sensor data-Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
Experience with modern computer vision techniques
Strong mathematical skills and understanding of probabilistic techniques
Fluency in C++ or Fluency in Python with a basic understanding of C++
Extensive experience with programming and algorithm design-Strong mathematics skills
Bonus Qualifications
Publications in your field (CVPR, ICCV, RSS, ICRA preferred)
Experience with autonomous robots
Experience with realtime sensor fusion (e.g. LiDAR, camera, radar)
Experience with novel pipelines and architectures for convolutional neural nets
Experience with 3D data and representations (pointclouds, meshes, etc.)
