6 days ago
Remote, Germany +3 moreSenior
Responsibilities
- Develop scalable software libraries for numerical methods and high-performance computing.
- Design, optimize, debug, and benchmark algorithms across CPU and GPU architectures using CUDA.
- Work with product management and internal and external partners to understand feature and performance requirements and contribute to library roadmaps.
- Provide technical leadership and guidance to library engineers.
- Identify performance and abstraction improvements that reduce software maintenance costs.
Requirements
- PhD or MSc degree in Computational Science, Computer Science, Applied Mathematics, or a related science or engineering field, or equivalent experience, is preferred.
- At least 12 years of experience developing, debugging, and optimizing high-performance parallel numerical applications on modern computing platforms with GPU acceleration using CUDA.
- Excellent C and C++ programming and software design skills.
- Experience leading and completing software development projects.
- Strong collaboration, communication, and documentation skills.
- Knowledge of CPU and/or GPU hardware architecture is preferred.
- Experience with CI/CD systems, JIRA, and project management tools is preferred.
- Experience working in a globally distributed organization is preferred.
- Advanced debugging, profiling, and testing skills for accuracy and performance are preferred.
- Experience with a scripting language, preferably Python, is preferred.
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.