10 days ago
Base Salary
$224k - $357k/yr
Responsibilities
- Develop scalable library software using modern tools and languages for numerical methods.
- Design, develop, optimize, benchmark, debug, and test algorithms across CPU and GPU architectures.
- Work with product management and internal and external partners to understand feature and performance requirements and contribute to library technical roadmaps.
- Provide technical leadership and guidance to library engineers.
- Identify opportunities to improve library performance, abstractions, and maintainability.
Requirements
- 12+ years of experience developing, debugging, and optimizing high-performance parallel numerical applications on modern computing platforms with GPU acceleration using CUDA.
- Excellent C/C++ programming and software design skills.
- Proven experience leading and completing software development projects.
- Excellent collaboration, communication, and documentation habits.
- A PhD or MSc degree in Computational Science, Computer Science, Applied Mathematics, or a related science or engineering field is preferred, or equivalent experience.
- Knowledge of CPU and/or GPU hardware architecture is desirable.
- Experience with debugging, profiling, and testing for accuracy and performance is desirable.
- Python scripting experience is desirable.
- Experience with CI/CD systems, Jira, and globally distributed organizations is desirable.
Benefits
- Hybrid work arrangement indicated by the #LI-Hybrid designation.
- Eligible for equity and benefits.
- Applications accepted at least until November 3, 2026.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.