LLM Application Intern, AV Infrastructure - 2025

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.

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• 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.

• 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.