Scene Understanding Autonomous Mobility

Scene Understanding for Autonomous Mobility - Honda Research Institute USA

Job Number: P25 F08

Honda Research Institute USA (HRI-US) is seeking a highly motivated Research Scientist to contribute scene understanding technologies for autonomous mobility. A successful candidate will focus on the research and development of scene understanding and perception algorithms and will have experience with one or more of the following: social cue recognition, semantic segmentation, action recognition, and SLAM. The ideal candidate combines strong research capabilities with practical experience deploying models in real-world systems.

Mountain View, CA

• Research on cutting-edge scene understanding algorithms using multimodal sensor data (e.g., camera, LiDAR).
• Develop and implement machine learning and deep learning models for behavior and intent prediction, social interation understanding and important agent identification.
• Design and implement deep learning algorithms to represent semantic information as quantitative information and vice versa.
• Publish scholarly articles to top-tier conferences and journals in robotics, computer vision, and machine learning.
• Ability to analyze existing perception software stack and implement improvements on physical systems.
• Collaborate with a dynamic team of researchers and engineers to integrate the algorithms with motion planning and controls.

• PhD in computer science, robotics, or a related field
• 2+ years of experience with machine learning and deep learning
• Experience with frameworks such as PyTorch or Tensor Flow
• Strong programming skills in Python or C++
• Experience with training, testing and fine tuning machine learning algorithms
• Experience with quantization, distillation, and other methods for improving runtime

• Experience with LLMs and Foundation models
• Experience in autonomous driving, robotics, or intelligent systems
• Familiarity with ROS and traffic simulators (e.g., Carla, Carmaker)
• Experience with developing end-to-end systems
• Experience with deploying models on a physical (robotic) platform
• Experience with optimization solvers