Sparsh Gupta

I’m a Machine Learning Developer focused on GenAI and RAG systems that are measurable, fast, and reliable. I build end-to-end pipelines—from preprocessing and retrieval to deployment—so teams can ship features with confidence.

In my internship, I built an automated employee check-in/check-out system using facial recognition, reaching 90%+ accuracy for 100+ employees and saving 6 hours of manual work daily. I designed the full facial recognition pipeline including face detection, embedding generation, database integration, and real-time attendance marking.

As a GenAI & ML Developer, I develop and evaluate ML models achieving 90%+ accuracy through data preprocessing, feature engineering, and model optimization. I also build RAG pipelines with LangChain, HuggingFace embeddings, and vector databases to deliver context-aware response generation within collaborative, multidisciplinary teams.

I love working closely with others—whether it’s collaborating with 5+ teammates on deployment or reviewing 10+ papers and organizing 3+ tech webinars. My work has earned recognition like Top 10 Performer (INCLUDE 4.0) and a finalist spot at DRISHTI-NE Hackathon, and I’m motivated to keep delivering AI products that reduce hallucinations and improve response quality.