NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
This is an outstanding opportunity to join NVIDIA, a company at the forefront of AI and high-performance computing. As a Senior / Principal Deep Learning Engineer — Model Evaluation & AI Systems, you will play a meaningful role in crafting the future of AI. Your work will have a direct impact on our product releases and positioning in the market.
What you'll be doing:
- Define and build evaluation methodologies for innovative AI models, including LLMs, RAG systems, agents, and vision/multimodal models.
- Build and expand NeMo Evaluator as an open-source platform, focusing on correctness, reproducibility, and ease of adoption.
- Build scalable, reproducible evaluation infrastructure, including harnesses, orchestration, and result pipelines running on large GPU clusters.
- Collaborate with and engage the open-source community, reviewing contributions, shaping the roadmap, and sharing best practices.
- Work alongside model training, inference, and product divisions to provide trusted evaluation signals that inform release and optimization decisions.
What we need to see:
- BS, MS, or PhD in Computer Science, AI, Applied Math, or a related field, or equivalent experience.
- Senior-level experience (typically 12+ years) developing or assessing contemporary machine learning and deep learning systems.
- Hands-on experience with large language models and NLP, including model behavior analysis and evaluation.
- Demonstrated experience contributing to open-source software or building platforms, libraries, or tools used by other engineers.
- Ability to take charge of unclear technical challenges and communicate effectively across research, engineering, and product teams.
Ways to stand out from the crowd:
- Experience building or improving evaluation frameworks, benchmarks, or ML infrastructure used by other teams or external users.
- A strong appreciation for evaluation quality, including correctness, reproducibility, and consistency across environments.
- Hands-on experience evaluating modern AI systems such as LLMs, RAG pipelines, agents, or multimodal models.
- Prior involvement in open-source projects, through contributions, reviews, maintenance, or community engagement.
- Experience acting as a technical bridge across teams or platforms (e.g., evaluation, training, or agent frameworks), combining architectural understanding with clear communication and influence. Join us and be part of a team that is defining the next era of computing with AI!
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until March 7, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering 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.