Intern, Deep Learning Engineer

Role overview

Key responsibilities

• Implement and benchmark next-generation architectures for multimodal perception, online mapping, behavior prediction, and world modeling.
• Own a targeted research project from data analysis through model verification under senior mentorship.
• Train, tune, and optimize deep learning models using large-scale compute clusters and truck datasets.

Required qualifications

• Currently pursuing a master’s or Ph.D. in computer science, robotics, or a related field focused on deep learning, computer vision, robotics, or a related area.
• Proficient in Python and PyTorch with clean coding practices.
• Understand modern AI architectures, especially Transformers and their applications.
• Available full-time for at least three months.

Preferred qualifications

• Academic thesis or project experience in multimodal perception, generative AI or diffusion, motion prediction, or end-to-end autonomous driving.
• Publications or submissions at conferences such as CVPR, ICCV, NeurIPS, ICLR, or ICRA.
• Experience with Linux, Git, C++, TensorRT, or ONNX deployment tools.