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Chirag Parmar

@chiragparmar2

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Machine learning intern building scalable NLP and computer vision solutions.

India

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What I'm looking for

I’m looking to work on real-world, production-ready AI—building and deploying scalable NLP/ML systems via APIs, improving model outcomes with experiments, and delivering reliable operations like I do in IT support.

I’m a Machine Learning Intern who builds multilingual and predictive AI systems end-to-end, from modeling to deployment. I developed a multilingual complaint intent classification system for UPSIDA using the MuRIL transformer and deployed it via a Flask REST API, reducing manual triage effort by 40% while processing 5,000+ monthly citizen grievances with consistent accuracy.

I also contribute to model improvement through strong ML workflows—working on predictive analytics with Python, scikit-learn, and TensorFlow for a 12% accuracy gain, and supporting an A/B testing pipeline that improved learner engagement by 18%. Alongside my ML work, I’ve supported 200+ end users in IT support, resolving 95% of Tier 1/2 tickets within SLA and managing VMware Horizon VDI with zero downtime—so I care deeply about reliability, production readiness, and measurable impact.

Experience

Work history, roles, and key accomplishments

IT Support Intern

VTech Solution

Feb 2026 - May 2026 (3 months)

Resolved 95% of Tier 1 and Tier 2 hardware and software tickets within SLA, supporting 200+ users across Windows and macOS and reducing average ticket resolution time by 30%. Managed VMware Horizon VDI environments, provisioning/decommissioning 50+ virtual desktops with zero downtime incidents and improving helpdesk SOPs to reduce repeat tickets by 25% and raise first-call resolution to 88%.

IT Support Troubleshooting VMWare Horizon VDI Windows Administration MacOS Support Software support

ML Intern - NLP

Kratitech

May 2025 - Aug 2025 (3 months)

Built a multilingual complaint intent classification system for UPSIDA using the MuRIL transformer model (English, Hindi, Hinglish), reducing manual triage effort by 40% across 5,000+ monthly grievances. Deployed the model via a Flask REST API delivering structured JSON predictions with high-confidence scores.

Python NLP MuRIL Flask JSON Model Serving

ML Intern - Predictive ML

Playpower Labs

Feb 2023 - Apr 2023 (2 months)

Developed and deployed ML predictive analytics models in Python using scikit-learn and TensorFlow, improving prediction accuracy by 12% over the prior baseline. Performed data cleaning and feature extraction on 20,000+ student behavior records, contributed to a recommendation engine, and helped implement an A/B testing pipeline that increased learner engagement by 18%.