Research Scientist: E2E Autonomous Mobility

Honda Research Institute USA; Mountain View (CA); In loco; USD 150.000 - 190.000; Tempo pieno

Descrizione del lavoro

Honda Research Institute USA in Mountain View, CA seeks a Research Scientist to advance end-to-end autonomous mobility—spanning perception, scene understanding, and driving policy. You will design end-to-end driving models, including vision-language-action and world models, and push improvements with simulation, data, and hardware experiments.

The role requires Ph.D. in a related field and hands-on DL experience with PyTorch or TensorFlow, plus proven ability to deploy models on real vehicles

Competenze

• Ph.D. in Computer Science, Robotics, Electrical Engineering, or related field.
• 2+ years of hands-on ML/DL experience with PyTorch or TensorFlow.
• Experience with end-to-end driving models, differentiable modules, or end-to-end training.
• Hands-on deployment/testing of models on real vehicle hardware (small-scale or full-scale).
• Strong programming skills in Python and/or C++.
• Strong publication record in robotics, CV, or ML.

Mansioni

• Research and develop end-to-end learning pipelines for autonomous mobility across perception, scene understanding, and driving policy.
• Design and train end-to-end driving models, including vision-language-action models and world models.
• Improve closed-loop performance through simulation, evaluation, and hardware iterations.
• Lead end-to-end hardware experiments on real vehicle platforms ( RoboRacer, F1TENTH, MuSHR,Duckietown).
• Publish research findings at top venues (RAL, ICRA, IROS, CoRL, CVPR, ICCV, ECCV, NeurIPS).

Conoscenze

End-to-end learning

Python

C++

PyTorch

TensorFlow

Research publication

Robotics/CV concepts

Formazione

Ph.D. in Computer Science/Robotics/EE or related field

Strumenti

ROS/ROS2

NVIDIA Jetson

vehicle sensor stacks

Descrizione del lavoro

Research Scientist: E2E Autonomous Mobility - Honda Research Institute USA

Research Scientist: E2E Autonomous Mobility

Job Number: P25F22

Honda Research Institute USA (HRI-US) is seeking a highly motivated Research Scientist to contribute end-to-end pipeline and learning technologies for autonomous mobility, spanning perception, scene understanding, planning and control. A successful candidate will have experience with one or more of the following: end-to-end driving model/stack, closed-loop performance improvement, end-to-end hardware experiments on real vehicles, vision-language-action models, world models, imitation or reinforcement learning for driving. The ideal candidate combines strong research capabilities with practical experience deploying models in real-world systems.

Mountain View, CA

Key Responsibilities

• Research and develop end-to-end learning pipelines for autonomous mobility, spanning perception, scene understanding, and driving policy.
• Design and train end-to-end driving models, including vision-language-action models, foundation models, world models, and imitation or reinforcement learning-based policies.
• Improve closed-loop performance through simulation, data-driven evaluation, and iterative model refinement withsimulation and hardware.
• Lead end-to-end hardware experiments on real vehicle platforms, from small-scale cars (e.g., RoboRacer; former F1TENTH) to full-scale vehicles.
• Contribute new research ideas and publish at top-tier venues (e.g., RAL, ICRA, IROS, CoRL, CVPR, ICCV, ECCV, NeurIPS)

Minimum Qualifications

• Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field
• 2+ years of hands-on experience in machine learning / deep learning with PyTorch or TensorFlow
• Research experience in one or more of: end-to-end driving model/stack, end-to-end training of differentiable modules, vision-language-action models, world models, imitation or reinforcement learning for driving, or closed-loop performance improvement
• Hands-on experience deploying and testing learned models on real vehicle hardware, including small-scale autonomous cars (e.g., RoboRacer;F1TENTH, MuSHR, Duckietown) and/or full-scale vehicles
• Strong programming skills in Python and/or C++
• Experience building end-to-end training and evaluation pipelines for perception or driving models
• Strong publication record in robotics, controls, computer vision, or machine learning

Bonus Qualifications

• Experience running closed-loop experiments on full-scale autonomous vehicles, including safety driver protocols and on-vehicle data logging
• Experience with ROS/ROS2, embedded compute (e.g., NVIDIA Jetson, DRIVE), and vehicle sensor stacks (camera, LiDAR, radar, IMU)
• Experience with model optimization for real-time on-vehicle inference (quantization, distillation, TensorRT)
• Experience with closed-loop simulation (e.g., CARLA, Waymax, NVIDIA Alpasim, Isaac sim) and sim-to-real transfer
• Experience with LLMs, VLMs, or foundation models for driving or scene understanding
• Experience with large-scale distributed training and multimodal datasets

Desired Start Date

April 2027

Position Keywords

E2E, Autonomous Driving, Closed-loop Performance