Our Deep Learning models performance engineering team at NVIDIA is hiring senior software engineers to help us build the libraries and tools that enable Deep Learning Researchers and Engineers to design, develop, and deploy efficient AI applications. We are an ambitious and diverse team that builds Transformer Engine - an open source library featuring optimizations boosting the performance at all levels of NVIDIA's AI stack. Our team has a wide collaborative footprint, working not only with multiple teams across NVIDIA but also with the broader open-source community to deliver SOTA Deep Learning performance on the best AI platform in the world!
What you'll be doing:
Own and evolve the build, packaging, and release infrastructure for Transformer Engine, ensuring reliable and reproducible delivery across platforms.
Drive developer productivity improvements through better tooling, automation, and CI/CD pipelines.
Maintain and improve the Python packaging of the Transformer Engine library, keeping pace with modern packaging standards and toolchains.
Identify and resolve issues across the entire AI software stack.
Engage with the open-source community as well as support enterprise customers and partners by delivering the benefits of NVIDIA’s latest hardware and software innovations.
This is a development-focused role that drives software quality and reliability without on-call duties.
What we need to see:
MS or PhD in Computer Science or Engineering (or equivalent experience)
5 + years of proven experience building or supporting large software projects or equivalent
Strong proficiency in Python, including packaging ecosystems (setuptools, pip, wheels, conda).
Expertise with scripting and automation (Bash, Python, or similar).
Experience in continuous build and release management for Linux systems
Experience building containerized applications
Ways to stand out from the crowd:
Proven experience shipping open-source software with many contributing teams
Experience with uv Python package manager
Experience with C++ build systems, including dependency issues, symbol resolution, and linking problems
Hands-on experience designing and maintaining automated workflows using tools like n8n or similar orchestration platforms.
Experience building and packaging CUDA applications, including managing toolkit versions, compiler compatibility, and GPU-aware build configurations.
You will also be eligible for equity and benefits.
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.#deeplearningTop Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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