Data Processing Developer Technology Intern - 2027

The Data Processing Developer Technology Intern role sits within NVIDIA's Developer Technology Team, a group that drives cutting‑edge advances in accelerated computing for AI and data‑intensive workloads. NVIDIA is a global leader whose AI infrastructure powers a wide range of industries, and the internship offers a chance to contribute to that impact while learning from top researchers and engineers. In this position you will explore and create methods to speed up deep‑learning, machine‑learning and other AI workloads on GPUs. You will collaborate with experts from both industry and academia to dissect and optimise complex AI and high‑performance‑computing algorithms for modern CPU and GPU platforms. Findings will be shared through developer blogs or conference presentations, and your insights will help shape the next generation of hardware, software and programming models alongside NVIDIA's research, hardware, system‑software, libraries and tools teams. The internship requires you to be actively enrolled in a PhD or Master program in Computer Science, Computer Engineering or a closely related computational discipline. You must be proficient in C/C++ development and possess a solid grasp of algorithms. A background in parallel programming, such as CUDA, OpenACC, OpenMP, MPI or pthreads, is essential. Strong communication and organisational abilities, a logical approach to problem solving, and effective time‑management and prioritisation skills are also mandatory. Additional strengths that will set you apart include demonstrated expertise in parallelising and optimising deep‑learning models for domains like natural‑language processing, computer vision or recommender systems, as well as a deep understanding of linear algebra. The internship runs until November 8 2026, with applications reviewed on a rolling basis, and NVIDIA emphasizes a diverse, inclusive workplace where all candidates are evaluated fairly. What the role asks for: - Currently pursuing PhD or Master in CS/CE or related field - Fluent in C/C++ programming with strong algorithm knowledge - Experience with parallel programming (CUDA, OpenACC, OpenMP, MPI, pthreads) - Effective communication and organizational skills - Logical problem‑solving approach - Good time‑management and prioritization abilities - Nice-to-have: expertise in parallelizing Deep Learning models (NLP, CV, recommender) - Nice-to-have: strong understanding of linear algebra