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Rinku Duhan

@rinkuduhan

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AI/ML engineer building LLM, multi-agent, and RAG systems for scalable, evidence-grounded solutions.

India

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What I'm looking for

I’m looking for a team where I can build production-ready AI/ML systems—especially LLM apps with RAG and agentic workflows—while owning end-to-end pipelines, clean APIs, and evidence-grounded outputs.

I’m an AI/ML engineer with hands-on experience building AI/ML pipelines, LLM-powered applications, multi-agent AI systems, and RAG-based solutions through research, internships, and production-oriented projects. I focus on turning data into reliable, automated workflows—grounded in evidence and designed for scalability.

In research, I built an automated geospatial processing pipeline for large-scale Urban Heat Island analysis and trained a U-Net CNN for anomaly prediction, delivering government-ready risk reports and authoring a conference submission. In applied work, I developed end-to-end AI/ML solutions across Generative AI, computer vision, forecasting, recommendation systems, and customer analytics, standardizing reusable preprocessing and modular ML workflows to accelerate experimentation.

Experience

Work history, roles, and key accomplishments

ML Research Intern

Space Technology Centre of Excellence (ST-CoE)

Feb 2026 - May 2026 (3 months)

Conducted a literature review to scope Urban Heat Island prediction for Indian climate monitoring. Built a geospatial processing pipeline from Landsat scenes, trained a U-Net CNN for anomaly prediction, and produced automated risk reports and a conference paper.

Geospatial Processes U Net Deep Learning

AI/ML Intern

Labmentix Pvt. Ltd.

Nov 2025 - Apr 2026 (5 months)

Developed multiple end-to-end AI/ML solutions across generative AI, computer vision, forecasting, recommendations, and customer analytics. Built an NLP sentiment feature-based customer satisfaction prediction model and standardized reusable ML preprocessing workflows.