Summer Research Intern, Edge Communications Processing with AI Accelerators

IBM

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Posted
6 days ago
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Confirmed live yesterday

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TL;DR · Summer Research Intern, Edge Communications Processing with AI Accelerators

Summer Research Intern 2027 - Edge communications processing with AI accelerators is a research internship within IBM Research focused on developing advanced AI-driven solutions for performant communication and computing systems at the edge. The intern will develop and optimize AI kernels, inference workloads, and signal-processing algorithms on custom accelerator architectures while performing performance analysis and benchmarking. The role involves mapping complex models onto specialized platforms to solve problems in wireless communications, 5G/6G networks, and integrated sensing and communications. Key technical requirements include proficiency in low-level software development, performance optimization, and mathematics. Candidates should possess experience with machine learning systems, computer architecture, DSP architectures, or FPGA-based implementations. The work addresses the critical challenge of implementing efficient AI inference and hardware-aware software optimizations for next-generation computing systems and edge intelligence applications.

What you'll do

  • Develop and optimize AI kernels and inference workloads for custom accelerator architectures.
  • Evaluate and benchmark performance, efficiency, and scalability across representative workloads.
  • Map signal-processing and communication algorithms onto specialized computing platforms.
  • Prototype and implement algorithms using low-level programming techniques and hardware-aware software optimization.
  • Identify new opportunities for AI acceleration in performant communication and computing applications at the edge.
  • Translate complex algorithms into highly efficient implementations for research projects.

What we're looking for

  • Master's Degree (preferred).
  • Strong programming skills in low-level software development and performance optimization.
  • Strong foundations in mathematics, algorithms, and numerical methods.
  • Experience with AI inference, machine learning systems, signal processing, or related computational workloads.
  • Familiarity with digital systems, computer architecture, accelerator architectures, DSP architectures, or FPGA-based implementations.
  • Demonstrated ability to independently develop, prototype, and evaluate complex technical solutions.
  • Experience in kernel development, performance analysis, and hardware/software co-design (preferred).

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