Data Processing Developer Technology Intern
NVIDIA
Data Processing Developer Technology Intern
NVIDIA
Designs the chips and software that power AI
We’re currently seeking for an internship position in the Data Processing Developer Technology team. Would you enjoy researching parallel algorithms to accelerate AI and Data Processing workloads on advanced computer architectures? Do you find it rewarding to identify and eliminate system bottlenecks to achieve the best possible performance on pioneering computer hardware? Could you be thrilled about an opportunity to partner with the developer community, working at the forefront of technology breakthroughs that contribute to the success of an industry leader like NVIDIA? If so, we invite you to consider an internship with the Developer Technology Team.
What you will be doing:
In this position, you will research and develop techniques to GPU accelerate workloads in deep learning, machine learning or other AI domains.
Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex AI and HPC algorithms to ensure optimal AI solutions on modern CPU and GPU architectures.
Publish and/or present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the developer community.
Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.
What we need to see:
Currently pursuing a PhD or Master degree in Computer Science, Computer Engineering, or related computationally focused science degree.
Programming fluency in C/C++ with a deep understanding of algorithms and software development.
A background that includes parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, etc.
Effective communication and organization skills, with a logical approach to problem solving, good time management, and prioritization skills.
Ways to stand out from the crowd:
Expertise in parallelization and performance optimization of Deep Learning models arising from Natural Language Processing, Computer Vision, Recommender Systems, etc.
Excellent understanding of linear algebra.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Applications will be accepted until November 8, 2026.
Please note: We will be reviewing applications on a rolling basis as they are submitted. Strong candidates may be contacted for next steps before the application deadline. We encourage you to apply early.
NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.
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