NVIDIA is an industry leader with groundbreaking developments in High-Performance Computing, Artificial Intelligence and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, autonomous cars and conversational AI that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company, and build our teams. Join us at the forefront of technological advancement!

NVIDIA is looking for a Senior Capability Development Engineer to develop the architecture of high-impact, high-visibility Large Language ModeI tools and enhance NVIDIA internal RAG and Agent platforms to improve productivity of Ops Engineering. If you're creative & passionate about solving real world conversational AI problems, come join our Ops engineering team.

What You’ll Be Doing:

• Develop, Train, Fine-tune, and Deploy (multimodal) large language models for various AI-based applications.

• Develop LLM-based applications for such as RAG, TEXT2SQL, Agents.

• Apply instruction tuning, reinforcement learning with verifiable rewards (RLVR), and parameter efficient fine-tuning such as LoRA to improve LLMs for various AI-based applications.

• Measure and benchmark model and application performance.

• Analyze model accuracy and bias and recommend the next course of action & improvements.

• Drive the gathering, building, and annotation of domain specific datasets to train LLMs for different tasks and applications

• Characterize performance and quality metrics across platforms for various AI and system components

• Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews

• Help innovate, identify problems, recommend solutions and perform triage in a collaborative team environment and collaborate with various teams on new tool features and improvements of existing tools.

What We Need To See:

• Master’s or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Applied Mathematics, or equivalent practical experience, along with over 8 years of relevant work experience

• Strong programming skills in Python, with solid foundations in software design, optimization, and clean, maintainable coding practices.

• Familiarity with AI coding assistants (e.g., Cursor, Copilot) and the ability to leverage vibe coding to quickly develop lightweight tools that accelerate core tasks.

• Deep understanding of ML/DL algorithms and frameworks, with hands‑on exposure to LLMs, diffusion models, and conversational AI technologies such as RAG, Text2SQL, Agents, Embeddings, and Rerankers.

• Practical experience training LLMs using frameworks such as TRL, VERL, or OpenRLHF, along with strong collaboration skills and the ability to influence and guide teams in a dynamic matrix environment.

Ways To Stand Out From The Crowd:

• Good at Systems Thinking.

• Profound experience with dataset cleaning and solid understanding of Data Mining

• Prior experience with RLVR/Continue Pre-training/SFT

• Profound experience with TEXT2SQL

• Rich experience with SW architecture designing

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working with us and our engineering teams are growing fast in some of the hottest state of the art fields: Deep Learning, Artificial Intelligence, and Large Language Models.

If you're a creative engineer with a real passion for robust and enjoyable user experiences, we want to hear from you. NVIDIA is committed to encouraging a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.