Internship
TL;DR
Key Takeaways
- Research and develop GPU-accelerated AI and data processing workloads.
- Analyze and optimize complex AI and HPC algorithms.
- Publish findings and influence future hardware/software design.
- Pursuing a Master's degree in Computer Science, Computer Engineering, or related field.
- Applications accepted until November 8, 2026.
About the Role
This internship is with the Data Processing Developer Technology team. You will research parallel algorithms to accelerate AI and Data Processing workloads on advanced computer architectures, identify and eliminate system bottlenecks, and contribute to industry-leading technology breakthroughs.
What you will be doing:
- Research and develop techniques to GPU accelerate workloads in deep learning, machine learning, or other AI domains.
- Work with technical experts to analyze and optimize complex AI and HPC algorithms for optimal AI solutions on modern CPU and GPU architectures.
- Publish and present optimization techniques in developer blogs or conferences.
- Influence the design of next-generation hardware architectures, software, and programming models in collaboration with NVIDIA teams.
What we need to see:
- Currently pursuing a 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.
- Experience with parallel programming (e.g., CUDA, OpenACC, OpenMP, MPI, pthreads).
- Effective communication and organization skills, with a logical approach to problem-solving, good time management, and prioritization skills.
Ways to stand out:
- Expertise in parallelization and performance optimization of Deep Learning models (e.g., Natural Language Processing, Computer Vision, Recommender Systems).
- Excellent understanding of linear algebra.