Requirements:

BS, MS, or PhD in Computer Science, AI, Applied Math, or related field, or equivalent experience.
10+ years of hands-on experience in AI for natural language processing (NLP) and large language models (LLMs).
Strong problem-solving, debugging, performance analysis, test design, and documentation skills.
Solid mathematical foundations and expertise in AI/DL algorithms.
Excellent written and verbal communication skills, with the ability to work independently and collaboratively in a fast-paced environment.

Nice to Haves:

Experience in accuracy evaluation of LLMs (OpenLLM Leaderboard or HELM).
Hands-on experience with inference and deployment environments like TensorRT, ONNX, or Triton.
Passion for DevOps/MLOps practices in deep learning product development.
Experience running large-scale workloads in high-performance computing (HPC) clusters.
Strong understanding of Linux environments and containerization technologies like Docker.

Collaborate closely with partners and the open-source community to deliver flagship models as highly optimized NVIDIA Inference Microservices (NIM).
Research and develop innovative deep learning methodologies to evaluate new model families across diverse domains.
Analyze, influence, and enhance AI/DL libraries, frameworks, and APIs with the best engineering practices.
Research, prototype, and build robust tools and infrastructure pipelines to support ground-breaking AI initiatives.

Opportunity to shape the future of AI at a fast-growing company.
Work on cutting-edge models with lightning-fast inference on powerful GPU clusters.
Gain early access to unreleased hardware and impact NVIDIA's roadmap and the broader AI landscape.
NVIDIA is committed to fostering a diverse work environment and being an equal opportunity employer.