Developer Technology Engineering Intern - Compute Performance

NVIDIA is seeking a Developer Technology Engineering Intern - Compute Performance to join its Compute Developer Technology (Devtech) team. The company is renowned for its work in cutting-edge fields such as Deep Learning, Artificial Intelligence, Autonomous Vehicles, and Supercomputing, making it a highly desirable employer in the technology industry. The intern's main responsibilities will involve researching and developing techniques to GPU-accelerate leading applications in high-performance computing. This includes working with key application developers to understand and solve current and future problems, optimizing core parallel algorithms and data structures, and contributing to both library development and direct application enhancements. The role also involves collaborating with various teams at NVIDIA, such as architecture, research, libraries, tools, and system software, to influence the design of next-generation technologies. To be considered for this role, candidates must be pursuing a MSc or PhD degree in an engineering or computer science-related discipline. Proficiency in programming languages such as C/C++ and/or Fortran, along with a deep understanding of software design, programming techniques, and algorithms, is essential. Strong mathematical fundamentals, including linear algebra and numerical methods, are also required. Experience with parallel programming, particularly CUDA C/C++ and OpenACC, is highly valued. Nice-to-have skills include domain expertise in areas such as telecommunications, medical imaging, machine learning, deep learning, or natural sciences. Strong communication and organization skills, with a logical approach to problem-solving, good time management, and task prioritization, are also beneficial. The role offers the opportunity to work in a diverse and inclusive environment, with a commitment to fostering a diverse work culture. What the role asks for: - Pursuing a MSc or PhD degree in an engineering or computer science related discipline. - Programming fluency in C/C++ and/or Fortran. - Strong mathematical fundamentals, including linear algebra and numerical methods. - Experience with parallel programming, ideally CUDA C/C++ and OpenACC. - Strong communication and organization skills. - Good time management and task prioritization skills.