NVIDIA is seeking a highly motivated and creative Large Language Model (LLM) Intern to join our Autonomous Vehicle (AV) Infrastructure team. As an intern, you will play a key role in developing and applying LLM solutions to address real-world challenges in AV applications, including road event triage, automated regression testing, analytics from vast road datasets, auto code review & generation, and more! This is a phenomenal opportunity to work on ground breaking AI technologies and contribute to the future of autonomous driving. What You'll Be Doing: + Collaborate with AV engineers and LLM researchers to design and implement LLM-based solutions for triaging AV road events, automating regression test case creation, and extracting insights from large-scale road data. + Fine-tune LLM models for various applications such as QA Robot in support channels, code generation, and intelligent code checking. + Develop infrastructure to support scalable and efficient LLM deployment, ensuring high performance, security, and reliability. + Assist in curating, cleaning, and organizing training datasets to improve model accuracy and relevance for AV-related tasks. + Continuously explore advancements in AI/ML technologies to improve the capabilities of LLM applications within the AV domain. What We Need to See: + Currently pursuing a degree in Computer Science, Electrical Engineering or a related field. + Strong programming skills in Python with experience in AI/ML frameworks (e.g., PyTorch or TensorFlow). + Familiarity with LLM techniques such as prompt engineering, fine-tuning, transfer learning, and vector databases. + Solid understanding of machine learning concepts (e.g., supervised learning, deep learning) and NLP techniques. + Experience with data processing pipelines: data cleaning, transformation, labeling, and secure storage. Ways to Stand Out from the crowd: + Hands-on experience with production-level deployment of LLMs or other AI models. + Experience building microservices or working with cloud-based infrastructure (e.g., AWS, GCP). + Familiarity with automated testing frameworks or QA tools for software validation. + Knowledge of SQL & NoSQL databases for managing large datasets efficiently. + Knowledge of autonomous vehicle technology or experience working with large-scale sensor or road data is a plus. Join us at NVIDIA to push the boundaries of what's possible in autonomous driving by leveraging the ground-breaking power of large language models! #deeplearning