Open to opportunities

Shreejit Magadum

@shreejitmagadum

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AI/ML engineer building real-time inference and practical ML systems.

India

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What I'm looking for

I’m looking for a role where I can ship end-to-end ML/NLP systems—building inference pipelines, retrieval + ranking, and reliable APIs—while working with AWS and modern backend tools.

I built and deployed a real-time ML inference pipeline at Keyence Corporation, exposing multi-sensor processing (speed, distance, angle) through REST APIs and hitting 98% accuracy.

I led feature extraction and preprocessing for time-series sensor data, cutting training time by 35% while pushing accuracy from 91% to 98% using SVM and Random Forest for multi-class classification.

I also containerized the pipeline with Docker and deployed it on AWS (EC2/S3) so inference stayed scalable and reproducible, and I improved Python-based automated data validation—reducing manual verification by 30%.

Beyond that, I’ve shipped projects like my IEEE-published corn leaf disease detection system using TensorFlow/Keras with ResNet/GoogleNet and Grad-CAM explainability, plus a Python/Flask custom search engine and an SHL assessment recommender with FastAPI, FAISS, sentence transformers, and Gemini.

Experience

Work history, roles, and key accomplishments

AI/ML Engineering Intern

Keyence Corporation

Feb 2024 - Jul 2024 (5 months)

Built and deployed a real-time ML inference pipeline processing multi-sensor data with 98% accuracy. Engineered feature extraction pipelines reducing training time by 35% and applied SVM and Random Forest models for multi-class classification.

Python SVM Random Forest Docker Data Validation Feature Extraction Time Series Analysis