Senior Deep Learning Engineer, LLM Accuracy Evaluation at NVIDIA

Requirements:

BS, MS, or PhD in Computer Science, AI, Applied Math, or related field, or equivalent experience, with 5+ years of industry experience.
3+ 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 both independently and collaboratively in a fast-paced environment.

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 to ensure consistency with best engineering practices.
Research, prototype, and build robust tools and infrastructure pipelines to support groundbreaking AI initiatives.

Outstanding opportunity to craft the future of AI in a fast-growing company.
Work with world-class software engineers and partners on advanced models with lightning-fast inference.
Access to enterprise-grade GPU clusters capable of hundreds of PetaFLOPS.
Gain early access to unreleased hardware and make a direct impact on NVIDIA's roadmap and the broader AI landscape.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer.