Research Engineer Intern - Perception, E2E Autonomous Driving

Santa Clara, CA

Plus

Plus is an AI-first global autonomous trucking technology company safely developing autonomous trucks for the roads of the world.

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We are seeking a highly motivated Research Intern to contribute to the development of next-generation end-to-end autonomous driving (E2E-AD) models inspired by recent advancements such as UniAD, VAD, and multi-task learning approaches. This internship provides a unique opportunity to work on unified, perception-to-planning architectures that integrate vision, sensor fusion, and control in a data-driven manner. The intern will work closely with researchers and engineers to develop models that enable self-driving vehicles to perceive, predict, and plan efficiently in real-world environments.

Responsibilities:

  • Conduct research on end-to-end autonomous driving architectures, focusing on unified perception, prediction, and planning models.
  • Implement and optimize multi-task learning approaches for driving tasks, including object detection, motion prediction, and trajectory planning.
  • Work with sensor fusion techniques combining multi-modal inputs (e.g., camera, LiDAR, radar) to improve perception and decision-making.
  • Develop spatio-temporal and motion planning transformers for holistic driving scene understanding
  • Train, fine-tune, and evaluate models using large-scale autonomous driving datasets and internal Plus datasets
  • Utilize simulators to test and validate models in diverse driving scenarios.
  • Optimize real-time inference and deployment of driving models for efficient execution on edge devices.
  • Contribute to research publications and open-source implementations of E2E-AD models.

Required Skills:

  • Pursuing MS or PhD in CS, EE, mathematics, statistics or related field
  • Thorough understanding of deep learning principles and familiarity with perception, prediction and planning models
  • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
  • Experience with computer vision and sensor processing techniques.
  • Strong analytical and problem-solving skills.

Preferred Skills:

  • Past experiences in projects involving design, training or fine-tuning of various autonomous driving related models
  • Familiarity with autonomous driving datasets (e.g., nuScenes, Waymo).
  • Hands-on experience with simulators like CARLA, AirSim, or equivalent.
  • Knowledge of robotics and motion planning algorithms is a plus.
  • Publication record in relevant venues (CVPR, ICLR, ICCV, ECCV, NeurIPS, AAAI, SIGGRAPH)
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Tags: Architecture Autonomous Driving Computer Vision Deep Learning ICLR Lidar Mathematics NeurIPS Open Source PhD Python PyTorch Radar Research Robotics Statistics TensorFlow Transformers

Region: North America
Country: United States

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