In this role, you will:
Design, develop, train and evaluate multi-sensor fusion based deep learning models to understand obstacles and environmental context
Understand and curate real and synthetic datasets to improve our models
Perform latency optimization and deploy models to our robot fleet
Build a deep understanding of Perception gaps and behavioral issues around difficult obstacle types in order to help plan and prioritize our work
Collaborate with Prediction/Planner team to deploy fully autonomous vehicles in environments with difficult and rare obstacles, extreme weather conditions, and complex driving scenarios
Qualifications:
5 years of industry experience or more
Proficiency in Python and some knowledge in C++
Deep Learning expertise, preferably with panoptic segmentation experience
Experience developing multi-sensor fusion algorithms for object detection, panoptic segmentation or object tracking
Familiar with Transformer architecture
Bonus Qualifications:
Technical leadership experience with software or machine learning teams
TensorRT or CUDA experience
Experience of 3DGS for 3D reconstruction or novel view synthesis
Top Skills
What We Do
Zoox is an autonomous mobility company that was founded to provide a safer, cleaner, and more enjoyable future on the road. To achieve that goal, the company has spent the past 10 years creating a purpose-built robotaxi that gives the world a better way to ride.
Why Work With Us
At Zoox, we are working to solve one of the greatest technological challenges of our generation.
From the beginning, we have been focused on our goal of reimagining transportation from the ground up. We are a mission-driven community of innovators working together to create a safer, cleaner, and more enjoyable future on the road.
Gallery
