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Employment type:
Full time
Experience required:
Intermediate
Salary
Salary not provided
About the company:
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
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