AI Engineer with 1+ years in Machine Learning & Generative AI
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AI Engineer with hands-on experience building and deploying production-ready machine learning and generative AI systems, including RAG-based chatbots, LLM applications, and real-time ML APIs. Strong foundation in data engineering, model optimization, and scalable backend systems using Python. Proven ability to reduce latency, improve model performance, and deliver business-impacting insights.
MCKV Institution of Engineering
B.Tech · AI and Machine Learning
August 1, 2021 – June 30, 2025
NEOXIA TECH LABS
JUNIOR DATA ENGINEER
July 1, 2025 – November 1, 2025
Kolkata, West Bengal, India
ITOBUZ TECHNOLOGIES
DATA SCIENCE AND AI ENGINEERING INTERN
September 1, 2024 – March 1, 2025
Kolkata, West Bengal, India
RAG-Based Medical Chatbot
June 26, 2026 – Present
Built a retrieval-augmented generation (RAG) chatbot for context-aware medical query responses. Integrated vector database (FAISS) for efficient document retrieval and improved response relevance. Achieved ~15s average response latency with optimized retrieval and prompt pipelines.
View ProjectSocial Media Content Generation
June 26, 2026 – Present
Developed an end-to-end generative AI pipeline combining LLM-based text generation and diffusion-based image synthesis. Enabled automated content creation with shared context-aware prompts across modalities. Exposed functionality via APIs and UI for real-time usage (~60s latency, optimized toward <30s).
Income Prediction & Socio-Economic Analysis
June 26, 2026 – Present
Performed EDA and statistical analysis (ANOVA, Chi-square) on 32K+ records to identify key income predictors. Built and evaluated classification models, achieving ~84.5% accuracy with an interpretable Decision Tree. Addressed class imbalance and improved model robustness using data preprocessing techniques.
Data Analytics with Python
IBM Skills Build
June 1, 2026 – Present
100 Days of Python
Udemy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects show a diverse application of AI, from medical chatbots to social media content generation and socio-economic analysis, indicating adaptability and broad interest. The experience in both data engineering and AI engineering roles, along with personal projects, suggests a strong drive for continuous learning and practical application. The target role of 'AI Engineer' aligns well with the candidate's demonstrated skills and project focus on building and deploying AI systems.
Soft Skills & Operational Fit
The candidate demonstrates a results-oriented approach, focusing on latency reduction and business impact. Collaboration with cross-functional teams is mentioned, indicating an ability to work in a team environment. The project descriptions suggest a proactive problem-solving mindset, particularly in optimizing AI pipelines.