Deep Learning Engineer, LLM Accuracy Evaluation - Remote

Overview

We are seeking senior engineers to pioneer new methodologies for accurately assessing the performance of ground-breaking deep learning models, including LLMs, RAG, agents, and vision models. You will collaborate across the organization to bring the latest flagship models from our community and partners—such as Gemma and Llama-3—to life as optimized NVIDIA Inference Microservices (NIM). This role offers an outstanding opportunity to craft the future of AI at a fast-growing company at the forefront of the AI revolution.

In Short

• Collaborate closely with partners and the open-source community.
• Deliver flagship models as highly optimized NVIDIA Inference Microservices (NIM).
• Research and develop innovative deep learning methodologies.
• Analyze and enhance AI/DL libraries, frameworks, and APIs.
• Build robust tools and infrastructure pipelines.
• Work on enterprise-grade GPU clusters capable of hundreds of PetaFLOPS.
• Gain early access to unreleased hardware.
• Make a direct impact on NVIDIA's roadmap and the broader AI landscape.
• Utilize problem-solving and performance analysis skills.
• Work in a fast-paced environment both independently and collaboratively.

Requirements

• BS, MS, or PhD in Computer Science, AI, Applied Math, or equivalent experience.
• 10+ years of hands-on experience in AI for NLP and LLMs.
• Strong problem-solving and debugging skills.
• Solid mathematical foundations and expertise in AI/DL algorithms.
• Excellent written and verbal communication skills.
• Experience in accuracy evaluation of LLMs.
• Hands-on experience with inference and deployment environments.
• Passion for DevOps/MLOps practices.
• Experience running large-scale workloads in HPC clusters.
• Strong understanding of Linux environments and containerization technologies.

Benefits

• Diverse work environment.
• Equal opportunity employer.
• Impactful work in AI and digital twins.
• Opportunities for growth and development.
• Access to cutting-edge technology and hardware.