NVIDIA
Technology
SeniorSoftwareEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer at NVIDIA. Skills: CUDA kernel engineering, Python library development, Geometric deep learning. Build CUDA kernels. Implement CUDA kernels”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
6+ years software engineering experience, CUDA and GPU programming background, Deep proficiency in C++, Experience building production libraries, Good foundation in GPU computing, BS/MS in Computer Science or related field or equivalent experience
Nice to Have
Contributed to major neural network framework, Hands-on Triton kernel development, Experience with mixed-precision design, PhD in computational chemistry or related field, Contributions to open-source projects
What You'll Do.
Implement CUDA kernels
Optimize CUDA kernels
Deliver GPU-accelerated primitives
Build interfaces for PyTorch
Build interfaces for JAX
Drive CI/CD infrastructure
Collaborate with Applied Science teams
Translate prototypes into kernels
Engage with framework developers
How You'll Work.
Team & Collaboration
Applied Science teams; Research teams; External framework developers; Third-party framework developers
Full 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 a diverse, supportive environment where everyone is inspired to do their best work. Join our group and discover how you can develop a lasting impact on the world. NVIDIA BioNeMo is building the computational foundation for the next generation of biological discovery. We are looking for a Senior Software Engineer to join the cuEquivariance team — an NVIDIA library that accelerates geometric neural networks on NVIDIA GPUs, enabling researchers in molecular biology, materials science, and physics to train and deploy equivariant models at scale. This team builds and ships the production GPU kernels and software interfaces that power equivariant deep learning throughout the scientific field. The work spans CUDA kernel engineering, Python library development involving both PyTorch and JAX, and direct collaboration with research teams and external framework developers. If you want to work where GPU computing meets graph-based deep learning, this is the role for you. Your work will run in production pipelines across the scientific community. **What You Will Be Doing:** * Build, implement, and optimize CUDA kernels for equivariant neural network primitives — tensor products, segmented polynomials, and triangle-based operations — targeting peak performance across NVIDIA GPU generations. * Be responsible for the end-to-end delivery of GPU-accelerated geometric ML primitives: from implementation to validated, production-quality software that external
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