Hi, I'm Henil Sureshbhai Diyora, a MS Computer Science candidate at the University at Buffalo, set to graduate in May 2026. I bring 13 months of industry ML experience in industrial IoT and have delivered 3 production-grade AI/ML projects spanning LLM agents, RAG pipelines, and deep learning.\n\nI am proficient in PyTorch, LangChain, Hugging Face, and MLOps tooling, and I am seeking full-time AI/ML Engineer or Data Scientist roles with OPT authorization.

Henil Sureshbhai Diyora

Hi, I'm Henil Sureshbhai Diyora, a MS Computer Science candidate at the University at Buffalo, set to graduate in May 2026. I bring 13 months of industry ML experience in industrial IoT and have delivered 3 production-grade AI/ML projects spanning LLM agents, RAG pipelines, and deep learning.\n\nI am proficient in PyTorch, LangChain, Hugging Face, and MLOps tooling, and I am seeking full-time AI/ML Engineer or Data Scientist roles with OPT authorization.

Available to hire

Hi, I’m Henil Sureshbhai Diyora, a MS Computer Science candidate at the University at Buffalo, set to graduate in May 2026. I bring 13 months of industry ML experience in industrial IoT and have delivered 3 production-grade AI/ML projects spanning LLM agents, RAG pipelines, and deep learning.\n\nI am proficient in PyTorch, LangChain, Hugging Face, and MLOps tooling, and I am seeking full-time AI/ML Engineer or Data Scientist roles with OPT authorization.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
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Work Experience

Data Scientist Intern at Intellithink Industrial IoT
May 1, 2023 - June 30, 2024
Developed and benchmarked ML models (SVM, Random Forest, XGBoost, KNN, ANN/MLP) for industrial fault prediction; achieved up to 92% accuracy with 23% lower compute cost. Engineered deep learning models (1D CNN, LSTM/GRU, Variational Autoencoders) for fault detection in noisy industrial signals, outperforming classical baselines by 20%. Built end-to-end time-series data pipeline with automated feature extraction, anomaly filtering, and quality validation, improving model training data quality by 82%. Implemented production model drift and data drift detection system; proactive retraining triggers reduced false alarm rates by 30%. Deployed real-time Machinery Health Indicator using clustering and one-class SVM; automated client alerting pipeline cut incident response time by 35%.

Education

Master of Science in Computer Science at University at Buffalo, State University of New York
August 1, 2024 - May 1, 2026
Bachelor of Technology in Computer Engineering at UKA Tarsadia University, Surat, India
July 1, 2020 - July 1, 2024

Qualifications

Add your qualifications or awards here.

Industry Experience

Software & Internet, Professional Services