NVIDIA is seeking a passionate and innovative AI Software Engineer to play a pivotal role in advancing our Copilots for Compute (C4C) initiative. This groundbreaking initiative will redefine how AI copilots support and accelerate our hardware and software stacks, shaping the direction of NVIDIA’s compute capabilities.

As part of this role, you’ll prototype and deploy next-generation AI copilots that push the boundaries of computing technologies. These copilots will transform the way compute-intensive workloads are managed, automate optimization tasks, streamline massive AI infrastructures, and accelerate the design of our next-generation chips. Your contributions will influence the flagship GPU and software roadmaps, driving productivity for both NVIDIA employees and customers, while advancing AI driven innovations across the industry.

What you'll be doing:

• Design, develop, and train AI co-pilot models, focusing on data curation, model fine-tuning, and seamless deployment for real-world use cases.

• Conduct innovative research and literature reviews of pioneering AI techniques, implementing functional prototypes that push technological boundaries.

• Build full-stack implementations of co-pilot models, optimizing their performance for various applications across software and hardware domains.

• Collaborate closely with diverse teams, including researchers, engineers, and product managers, to ensure mission goals are met and exceeded.

• Drive comprehensive testing and evaluation of models, using metrics to drive improvements and ensure reliability and performance.

• Perform code reviews and promote best practices in code quality and software development processes.

What we need to see:

• Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Applied Mathematics, or a related field—or equivalent experience.

• Experience in PyTorch, Python, and modern software development practices.

• Strong foundation in deep learning and hands-on experience with Large Language Models (LLMs) and Reinforcement Learning.

• Excellent communication and interpersonal skills to articulate complex technical concepts and collaborate effectively with cross-functional teams.

Ways to stand out from the crowd:

• Proven contributions in developing AI systems for software, hardware, or large-scale computing environments.

• Expertise in C++, CUDA, or GPU programming, with a deep understanding of chip design and computer architecture.

• Experience with GenAI and cutting-edge LLM technologies, and familiarity with the intersection of AI and hardware design.