Tobechukwu Ikenwe

Experience

Building practical experience across AI systems, machine learning, and embedded AI.

AI Systems Engineering Intern

MathWorks·Remote·Aug 2026 – Present
  • •Developing an AI-powered predictive maintenance system to diagnose bearing faults from vibration sensor data for resource-constrained embedded systems.
  • •Building a deep learning pipeline to classify normal, inner-race, and outer-race bearing faults from segmented vibration signals.
  • •Applying pruning, projection, and quantization to optimize models for embedded deployment while analyzing accuracy, model size, memory, and inference latency.

Cornell Tech AI Fellow

Cornell University·Remote·Mar 2026 – Present
  • •Selected as 1 of 1,000 fellows from 5,300+ applicants for an intensive AI program focused on building a strong foundation in machine learning, deep learning, NLP, and modern AI systems.
  • •Developed hands-on understanding of the ML lifecycle, from exploratory data analysis and feature engineering to training, model selection, evaluation, and deployment using supervised learning and neural networks.
  • •Built practical AI systems spanning LLMs, RAG, multimodal AI, and autonomous agents, developing the foundational intuition needed to reason about how modern AI systems learn, retrieve information, and execute workflows.