As a Research Engineer Intern - Vision-Language Models for E2E Autonomous Driving, you'll explore the potential of vision-language models to enhance reasoning, scene understanding, and interpretability in end-to-end autonomous driving. You'll have the opportunity to work towards a publication at a top tier venue by contributing to key areas of model development, including curating both real-world and synthetic training data, fine-tuning foundational vision-language models, and designing robust evaluation frameworks. Responsibilities: * Lead model development efforts using vision-language models for end-to-end autonomous driving systems * Curate high-quality training datasets from both real-world trips and synthetic sources * Optimize model architectures and fine-tune pre-trained foundational models to enhance performance and adapt to specific challenges * Design and implement evaluation frameworks to rigorously assess model performance in real-world driving environments Required Skills: * Pursuing MS or PhD in CS, EE, mathematics, statistics or related field * Thorough understanding of deep learning principles and familiarity with vision language models * 2-3 years experience with implementing and training deep learning models in at least one deep learning framework (PyTorch, Tensorflow, Jax) Preferred Skills: * Past experiences in projects involving design, training or fine-tuning of vision language models and familiarity with knowledge distillation, quantization, vLLM * Past experiences in deep learning projects related to autonomous driving * Publication record in relevant venues (CVPR, ICLR, ICCV, ECCV, NeurIPS, AAAI, SIGGRAPH) $19 - $65 an hour Our internship hourly rates are a standard pay determined based on the position and your location, year in school, degree, and experience.