In this role, the intern will contribute to the ML algorithm development and validation of the early sensor fusion based instance segmentation task.
Activities include developing early sensor fusion instance segmentation methods to improve long-tail instance segmentation performance for Perception in Autonomous Driving, developing effective metrics and evaluating algorithm performance with these metrics, and optimizing model inference efficiency.
Technical Qualifications & Language Requirements
Experience with one or more CV/ML tasks including 3D object detection, BEV semantic segmentation or instance segmentation, 3D scene completion and video understanding in 4D (3D+time).
Experience with applying Transformer to solve CV/ML problems.
Experience writing high quality Python/PyTorch code.
Experience writing C++ software.
Computer Science or Electrical Engineering background with M.
S or PhD degree.
Bonus Requirements
GPU/CUDA programming experience
Experience working with LiDAR, Camera and Radar data
Experience in algorithm development for Autonomous Driving software
Compensation
The monthly salary range for this position is $6,175 to $9,500.
Compensation will vary based on role, degree level and type, and benefits will be offered based on eligibility.
Additional benefits may include medical insurance, 401k, and a housing stipend.
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.
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A Final Note:
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.
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