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AI Research Engineer with less than a year in Machine Learning & Cloud
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Results-driven M.Tech Software Engineering Student with strong hands-on expertise in Python, Machine Learning, Deep Learning, Cloud Technologies and Generative AI. Delivered end-to-end ML/AI projects achieving up to 95% model accuracy, including a patent-published research under AI & Healthcare. Proficient in building and deploying data-driven applications using Flask, FastAPI, and AWS. Certified by Tata, Infosys and Microsoft Azure. Seeking a challenging role to apply AI and data science skills to build, solve real-world problems.
Vellore Institute of Technology
M.Tech Integrated · Software Engineering
August 1, 2021 – April 1, 2026
Fetal Health Classification, Data Profile, Boruta & Model Stacking
January 1, 2026 – April 1, 2026
Challenge: CTG datasets (2,126 records, 21 features) suffer from class imbalance and redundant features, causing baseline models to misclassify pathological cases at 28% false-positive rate. Applied Boruta feature selection to reduce from 21 to 11 features and stacked ensemble (Random Forest + XGBoost + Logistic meta-learner).Lifting F1 Score on the minority class from 0.71 to 0.89 and overall accuracy to ~95%. Reduced false positives from 28% to 8% via hyperparameter tuning with 5-fold cross-validation, directly improving clinical triage precision by 15%.Published a patent under AI & Healthcare domain, demonstrating novel contribution; research validated against industry standards.
AI Agent to Answer E-Commerce Data Questions
June 1, 2025 – December 1, 2025
Challenge: Non-technical e-commerce stakeholders needed data insights but lacked SQL skills, causing a 2-3 day lag per ad-hoc report. Built a Gemini API-powered NL-to-SQL agent with automated CSV ingestion, SQLite backend and Plotly visualisations; reduced ad-hoc data retrieval time from ~3 days to under 1 hour (60% faster) across a 50K-row dataset.Deployed RESTful endpoints via Flask and FastAPI supporting 10+ concurrent users; reduced manual reporting effort by 40% by replacing static Excel exports with live query-driven dashboards.
View ProjectSarpaanch AI – Stock Price Prediction
January 1, 2025 – May 1, 2025
Challenge: Single-model stock predictors for NSE equities showed directional accuracy below 75% on unseen test windows. Benchmarked 5 algorithms (Linear Regression, Random Forest, Extra Trees, KNN, XGBoost); selected LSTM+RNN ensemble as best-performer, achieving 92% directional accuracy vs. 74% XGBoost baseline.Deployed Streamlit app on AWS EC2; reduced inference response latency by 30% (from 2s to 1.4s) via model serialization optimisation; minimized MAPE forecasting error by 18% through ensemble averaging and hyperparameter search.
View ProjectTata Virtual Internship – GenAI Powered Data Analytics Job Simulation
Tata
June 1, 2026 – Present
Infosys - Exploratory Data Analysis
Infosys
June 1, 2026 – Present
Microsoft Azure AI Fundamentals (AI-900)
Microsoft Azure
June 1, 2026 – Present
Power BI - Microsoft Certified
Microsoft
June 1, 2026 – Present
Patent Published (AI & Healthcare)
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong alignment with the 'AI Research Engineer' role, focusing on research, model development, and deployment. The diversity of projects (finance, e-commerce, healthcare) shows adaptability and a broad interest in applying AI across different domains. The certifications further validate a proactive approach to skill development. The lack of professional experience means cultural fit is primarily inferred from project descriptions and certifications, which suggest a motivated and technically curious individual.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset, focusing on challenges and quantifiable outcomes. The patent publication suggests a drive for innovation and a commitment to rigorous research. The ability to deploy applications and optimize performance points to a practical, results-oriented approach. However, without direct work experience, assessing stress handling, team collaboration, and direct communication clarity in a professional setting is difficult.