Image and Data Processing Libraries Intern

3 Months ago • Upto 1 Years • Research & Development

Job Summary

Job Description

As an Image and Data Processing Libraries Intern at NVIDIA, you'll collaborate on the development of GPU-accelerated libraries used worldwide. Responsibilities include implementing new image and data processing algorithms, defining APIs, analyzing performance, handling numerical corner cases, and general software engineering tasks. You will work with senior engineers, researching state-of-the-art algorithms for image and data compression and processing, improving existing implementations, and understanding software use cases and requirements. This internship offers mentorship and the chance to contribute to cutting-edge technology impacting diverse industries.
Must have:
  • C/C++, Python programming skills
  • Parallel/GPU programming experience (CUDA, OpenCL)
  • Image coding (jpg, tiff) or data compression (LZW, DEFLATE) experience
  • Algorithm development and performance analysis
Good to have:
  • Knowledge of image processing algorithms
  • Performance analysis and test design skills
  • Floating-point arithmetic and numerical error analysis

Job Details

Around the world, leading commercial and academic organizations are using GPU to redefine AI, scientific and engineering simulations, and data analytics. Did you know that the GPU accelerated libraries developed by NVIDIA are used in such industries such as healthcare, VR, autonomous vehicles, social media, and e-commerce? If the idea of contributing to these excite you, come join our team and help us build accelerated software libraries which are used by the entire world.

In this role you will be part of our team responsible for the development of libraries that provide groundbreaking functionality and performance. The internship may include extending the capabilities of existing as well as building new libraries that will be used in various AI and HPC applications. It will involve working with senior software engineers who will provide mentorship and guidance.

The project will include implementing new image and data processing algorithms, defining APIs, analyzing performance, finding appropriate solutions for difficult numerical corner cases, and other general software engineering work.
 

What you’ll be doing:
  • Collaborating with team members and other partners to understand software use cases and requirements.
  • Research, analyze, and document state-of-the art algorithms
  • Develop algorithms for image and data compression and processing
  • Analyze and improve performance of existing implementations

What we need to see:

  • Pursuing a degree in Computer Science, Artificial Intelligence, Applied Math, or related field
  • Programming skills (C/C++, Python)
  • Parallel or GPU programming experience (AVX, NEON, OpenMP, MPI, CUDA or OpenCL)
  • Experience with image coding (jpg, tiff, etc) or data compression algorithms (LZW, DEFLATE, etc)
Ways to stand out from the crowd:
  • Knowledge of image processing algorithms
  • Performance analysis and test design skills
  • Familiarity with floating-point arithmetic internals and numerical error analysis.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative andautonomous, we want to hear from you!
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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About The Company

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

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