Research Intern (Deep Learning), 2026 Spring (Master / PhD)

Founded in 2016 in Silicon Valley, Pony.ai has quickly become a global leader in autonomous mobility and is a pioneer in extending autonomous mobility technologies and services at a rapidly expanding footprint of sites around the world. Operating Robotaxi, Robotruck and Personally Owned Vehicles (POV) business units, Pony.ai is an industry leader in the commercialization of autonomous driving and is committed to developing the safest autonomous driving capabilities on a global scale. Pony.ai’s leading position has been recognized, with CNBC ranking Pony.ai #10 on its CNBC Disruptor list of the 50 most innovative and disruptive tech companies of 2022. In June 2023, Pony.ai was recognized on the XPRIZE and Bessemer Venture Partners inaugural “XB100” 2023 list of the world’s top 100 private deep tech companies, ranking #12 globally. As of August 2023, Pony.ai has accumulated nearly 21 million miles of autonomous driving globally. Pony.ai went public at NASDAQ in Nov. 2024.

Responsibility

• Work with experts in the field of self-driving vehicles on designing and developing large-scale foundation models trained on vast amounts of real world data.
• Frame the open-ended real-world problems into well-defined ML problems; develop and apply cutting-edge ML approaches (deep learning, reinforcement learning, imitation learning, etc) to these problems; scale them to data pipelines; and streamline them to run in real-time on the cars.
• Develop and deploy deep learning models, including vision language models (VLMs) and Large Language Models (LLMs)
• Design and implement multi-modality and multi-task models focusing on 3D object detection and tracking, segmentation, semantics understanding, video understanding, scene understanding, traffic control, or trajectory prediction, etc.
• Optimize deep learning models to run robustly under tight run-time constraints.

Requirements

Preferred Experience

Note

This position is fully onsite in Fremont, at least 3 months.

Compensation

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