
AI Engineer with less than a year in Computer Vision & NLP
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Full-stack AI/ML engineer and data science practitioner with a strong research interest in applied machine learning, deep learning, and intelligent systems. Experienced in building end to end AI products from data pipelines and model development to production deployment with a focus on computer vision, NLP, and LLM powered applications. Actively pursuing research opportunities at the intersection of AI and high impact domains including healthcare and legal intelligence, with demonstrated ability to build research grade systems and recognition in national level competitions.
National Institute of Technology Durgapur
Bachelor of Technology · Mechanical Engineering
August 1, 2024 – May 1, 2028
Holy Garden Model School
Higher Secondary Certificate, Class XII, CBSE
August 1, 2021 – June 1, 2023
Jawahar Navodaya Vidyalaya
Secondary School Certificate, Class X, CBSE
July 1, 2016 – May 1, 2021
NeuroScan AI | Alzheimer's Disease MRI Classification System
January 1, 2025 – December 31, 2025
Achieved 99.84% accuracy across 4 Alzheimer's disease stages by building a ConvNeXt classification pipeline with 5-fold cross-validation ensemble and test time augmentation on structural brain MRI scans. Reduced diagnostic false positives by 30% by implementing Grad-CAM++ explainability visualizations, providing clinical grade attention heatmaps for radiologist validation and model interpretability. Deployed a production ready web application with one click MRI upload and real time inference by containerizing the full inference pipeline using Docker and serving it via a Flask REST API with Hugging Face Hub model integration.
View ProjectEasy Analyst | Enterprise NL-to-SQL Analytics Platform
January 1, 2025 – December 31, 2025
Reduced analytical query response time by ~97% (to <50ms) for repeated questions by implementing Redis semantic and exact match caching over a Vanna AI + BigQuery NL to SQL backend with LLM self healing on SQL execution errors. Enabled zero SQL business analytics for non technical users by building a multi tenant FastAPI + React platform with an RLHF feedback loop, per tenant ChromaDB vector isolation, and JWT-secured Improved AI query accuracy progressively over time by designing a Reinforcement Learning from Human Feedback pipeline that ingests corrected SQL pairs directly into each tenant's ChromaDB partition as few shot training examples.
View ProjectSAE Collegiate Club: Junior Coordinator, Robotics and ML Domain; organized Aarohan technical event for 200+ participants.
SAE Collegiate Club
June 1, 2026 – Present
Smart India Hackathon 2025: Selected as Semi Finalist among 10,000+ teams in SIH, representing NIT Durgapur with an AI driven solution.
Unknown
January 1, 2025 – Present
SAKSHAM National Competition 2021: State Level Winner by Petroleum Conservation Research Association, competing against 500+ participants.
Petroleum Conservation Research Association
January 1, 2021 – Present
All India Painting Contest 2019-20: Gold Medal winner among 1,000+ participants by Consumers India.
Consumers India
January 1, 2019 – Present
Cultural Fit Analysis
The candidate's project diversity, spanning medical imaging (NeuroScan AI) and enterprise analytics (Easy Analyst), shows a broad interest and adaptability, which is a positive indicator for cultural fit. Their active participation in clubs and competitions (SAE Collegiate Club, Smart India Hackathon) suggests a proactive and engaged individual who can contribute to a dynamic team environment. The focus on building practical, impactful AI solutions aligns well with a product-driven culture. However, the lack of professional work experience means their adaptability in a corporate setting is yet to be fully tested.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving, critical thinking, and research skills through their project work and achievements. Their involvement in organizing events and hackathons suggests good team collaboration and leadership potential. The detailed project descriptions indicate an ability to document technical work clearly. These soft skills are well-aligned with the demands of a senior AI engineering role, which often requires independent problem-solving and collaborative development.