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!