NVIDIA is hiring passionate, world-class computer scientists to work in its Compute Developer Technology (Devtech) team.
What you will be doing
In this role, you will research and develop techniques to GPU-accelerate leading applications in high performance computing fields within scientific computing, computational engineering, and data science. You will be performing in-depth analysis and optimization to ensure the best possible performance on current and next-generation GPU architectures. This involves:
- Working directly with key application developers to understand the current and future problems they are solving, crafting and optimizing core parallel algorithms and data structures to provide the best solutions using GPUs, through both library development and direct contribution to the applications.
- Collaborating closely with diverse groups at NVIDIA such as the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models, by investigating the impact on application performance and developer productivity.
What we need to see
- A BS, MS, or PhD degree from a leading university in an engineering or computer science related discipline. While not a requirement, domain expertise in telecommunications, medical imaging, machine learning, deep learning, or natural sciences is helpful.
- Programming fluency in C/C++ and/or Fortran with a deep understanding of software design, programming techniques, and algorithms.
- Strong mathematical fundamentals, including linear algebra and numerical methods.
- Experience with parallel programming, ideally CUDA C/C++ and OpenACC.
- Strong communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills.
You will need to travel from time to time for conferences and for on-site visits with developers.