Research Intern - Deep Learning

Summary

Pony.ai is a global leader in autonomous mobility, focusing on the development of safe autonomous driving technologies. The Research Intern will work with experts to design and develop large-scale foundation models and apply cutting-edge machine learning approaches to real-world problems in self-driving vehicles.

Responsibilities

• 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 perception 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

Skills

• Currently pursuing a Masters or PhD program in Computer Science, Machine Learning, Robotics, or similar field
• Strong background in deep learning, with experience in model design, training and evaluation
• Experience with deep learning research and tools
• Proficiency in software design and development using Python and C++
• Experience working with large-scale datasets, data preprocessing, and pipeline management
• Publications on top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/ICLR/AAAI
• Experience in applying ML/DL for behavior prediction, imitation learning, motion planning
• Experience in deploying deep learning algorithms for real time applications, with limited computing resources
• Experience in convex optimization, computational geometry or linear algebra
• Experience in GPU/CUDA/TensorRT
• Previous internships involving large-scale deep learning models and systems

Qualifications

Must Haves

• Currently pursuing a Masters or PhD program in Computer Science, Machine Learning, Robotics, or similar field
• Strong background in deep learning, with experience in model design, training and evaluation
• Experience with deep learning research and tools
• Proficiency in software design and development using Python and C++
• Experience working with large-scale datasets, data preprocessing, and pipeline management

Nice to Haves

• Publications on top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/ICLR/AAAI
• Experience in applying ML/DL for behavior prediction, imitation learning, motion planning
• Experience in deploying deep learning algorithms for real time applications, with limited computing resources
• Experience in convex optimization, computational geometry or linear algebra
• Experience in GPU/CUDA/TensorRT
• Previous internships involving large-scale deep learning models and systems