Summer Research Intern 2027

About the Role

IBM Research is seeking a Summer Intern to contribute to the development of advanced AI-driven solutions for performant communication and computing systems at the edge. This research internship sits at the intersection of AI systems, signal processing, and computer architecture.

Key Responsibilities

• Develop and optimize AI kernels and inference workloads for custom accelerator architectures.
• Evaluate and benchmark performance, efficiency, and scalability across representative workloads.
• Explore mappings of signal-processing and communication algorithms onto specialized computing platforms.
• Prototype and implement algorithms using low-level programming techniques and hardware-aware software optimization.
• Collaborate with researchers across AI systems, computer architecture, and communications domains.
• Contribute to the identification of new opportunities for AI acceleration in performant communication and computing applications operating at the edge.
• Example application areas include wireless signal processing, 5G/6G communications, integrated sensing and communications (ISAC), and AI-enhanced network intelligence.

Requirements & Tech Stack

• Strong programming skills and experience with 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.

Preferred Technical And Professional Experience

• Experience implementing and optimizing algorithms on custom computing platforms, accelerators, FPGAs, DSPs, or related systems.
• Familiarity with AI accelerator architectures, domain-specific architectures, or hardware/software co-design methodologies.
• Experience with kernel development, performance analysis, profiling, and benchmarking.
• Knowledge of machine learning models and inference frameworks.
• Background in wireless communications, communication systems, computer vision, sensor processing, or related domains.
• Demonstrated research experience through publications, open-source contributions, or significant technical projects.

Preferred Education

• Master's Degree