Unclassified - Cambridge, MA

posted about 1 month ago

Full-time - Entry Level
Cambridge, MA

About the position

The candidate will join the perception team, focusing on the research, design, and development of deep learning models aimed at enhancing scene understanding, object detection, tracking, and prediction for autonomous trucks. This role is critical in advancing the capabilities of autonomous systems through innovative deep learning techniques.

Responsibilities

  • Research and develop deep learning models for scene understanding.
  • Design algorithms for object detection and tracking.
  • Implement prediction models for autonomous trucks.
  • Optimize model inference using TensorRT and CUDA programming.

Requirements

  • Strong expertise in modern deep learning, computer vision, or robotics in areas such as 2D/3D segmentation and object detection.
  • Experience with visual/LiDAR based tracking and multi-object tracking (MOT) using deep learning.
  • Knowledge in behavior prediction techniques.
  • Ph.D. degree or a Master's degree with a solid research background is required.

Nice-to-haves

  • Deep knowledge and experience in reinforcement learning (RL) and inverse reinforcement learning (IRL).
  • Experience with Variational AutoEncoders (VAE) and Conditional Variational AutoEncoders (CVAE).
  • Familiarity with large language models and foundation models.
  • Proven track record of research publications as the first author in top conferences and/or journals.
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