20 hours ago
Remote, Germany or Remote, SwitzerlandSenior
Responsibilities
- Research and develop techniques to GPU-accelerate deep learning, machine learning, and other AI workloads.
- Analyze and optimize complex AI and HPC algorithms for modern CPU and GPU architectures.
- Identify and eliminate system bottlenecks through low-level performance optimization.
- Publish or present optimization techniques through developer blogs and relevant conferences.
- Collaborate with research, hardware, system software, libraries, and tools teams to influence next-generation architectures, software, and programming models.
- Partner with technical experts from industry and academia and engage with the developer community.
Requirements
- Advanced degree in Computer Science, Computer Engineering, or a related computationally focused science field, or equivalent experience.
- 8+ years of relevant software development or research experience.
- Programming fluency in C and C++ with a deep understanding of algorithms and software development.
- Background in parallel programming, such as CUDA, OpenACC, OpenMP, MPI, or pthreads.
- Hands-on experience with low-level performance optimization.
- In-depth understanding of CPU and GPU architecture fundamentals.
- Effective communication, organization, problem-solving, time-management, and prioritization skills.
- Preferred: expertise in parallelization and performance optimization of deep learning models for natural language processing, computer vision, or recommender systems.
- Preferred: excellent understanding of linear algebra.
Tech Stack
CC++
Categories
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.