Job description

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 an inclusive, 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. Join NVIDIA’s Modular Diagnostics team and lead AI-powered innovation. Our team develops key diagnostic applications and infrastructure to test every NVIDIA GPU. This ensures flawless performance before launch. As part of the Senior Software Engineer, AI Infrastructure Solutions team you will build intelligent automation. This automation speeds up critical engineering workflows and improves GPU validation speed and quality. What you'll be doing: • Build and deliver agentic AI solutions—autonomous systems that reason, plan, and take actions. These automate silicon bring-up, test and validation frameworks, debugging, and engineering workflows to speed up GPU launches. • Build scalable AI infrastructure, services, APIs, and reusable platforms that enable teams across NVIDIA to develop and deploy AI-powered applications. • Integrate AI agents with engineering tools, knowledge bases, data platforms, and existing business processes to build end-to-end intelligent workflows. • Partner with multi-functional teams across Modular Diagnostics and adjacent organizations to identify high-impact use cases, define requirements, develop prototypes, and deploy production-ready solutions. • Establish evaluation, observability, security, and reliability practices for AI systems to ensure solutions perform at scale and meet enterprise standards. • Drive projects from concept through adoption, measure their impact against clear success criteria, and continuously improve their efficiency. What we need to see: • BS or MS degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience. • 5+ years delivering production software, infrastructure, platform, or AI solutions. • Strong programming skills in Python and C/C++. • Track record of building applications with large language models, AI agents, retrieval-augmented generation, tool use, or workflow orchestration. • Demonstrated ability to build scalable services, APIs, data pipelines, and production software infrastructure. • Strong problem-solving, debugging, and system-design skills with a history of shipping reliable systems. • Effective collaboration across technical and business teams, with clear communication and the ability to drive solutions from idea to production. Ways to stand out from the crowd: • Background in GPU computing, CUDA, GPU architecture, or silicon bring-up processes. • Familiarity with engineering diagnostics, hardware development workflows, or systems software. • Hands-on work with MLOps, model evaluation frameworks, AI observability tools, or production AI monitoring. • Contributions to open-source AI/ML projects or developer tools. • Prior work building internal developer platforms or engineering efficiency tooling. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 26, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive 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.

Requirements

Must-haves

Build scalable AI infrastructure, services, APIs, and reusable platforms that enable teams across NVIDIA to develop and deploy AI-powered applications.
Integrate AI agents with engineering tools, knowledge bases, data platforms, and existing business processes to build end-to-end intelligent workflows.
Partner with multi-functional teams across Modular Diagnostics and adjacent organizations to identify high-impact use cases, define requirements, develop prototypes, and deploy production-ready solutions.
Establish evaluation, observability, security, and reliability practices for AI systems to ensure solutions perform at scale and meet enterprise standards.
Drive projects from concept through adoption, measure their impact against clear success criteria, and continuously improve their efficiency.
BS or MS degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
5+ years delivering production software, infrastructure, platform, or AI solutions.
Strong programming skills in Python and C/C++.
Track record of building applications with large language models, AI agents, retrieval-augmented generation, tool use, or workflow orchestration.
Demonstrated ability to build scalable services, APIs, data pipelines, and production software infrastructure.
Strong problem-solving, debugging, and system-design skills with a history of shipping reliable systems.
Effective collaboration across technical and business teams, with clear communication and the ability to drive solutions from idea to production.
Background in GPU computing, CUDA, GPU architecture, or silicon bring-up processes.
Familiarity with engineering diagnostics, hardware development workflows, or systems software.
Hands-on work with MLOps, model evaluation frameworks, AI observability tools, or production AI monitoring.
Contributions to open-source AI/ML projects or developer tools.
Prior work building internal developer platforms or engineering efficiency tooling.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until October 26, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aipythonml

Platform: eightfold
Effort: medium

Benefits

Benefits detected in the listing.

Vision