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IIT Madras || AI Engineer ❤️
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
agentic-ai-hands-on
April 21, 2026 – Present
This Repo is for practicing agentic ai from scratch
View Projectkapa-inspired-rag-mcp
April 14, 2026 – Present
Production grade RAG SaaS with multi-tenant auth, semantic caching, LLMOps observability (Prometheus/Grafana), per-tenant token cost tracking, and rate limiting - inspired by Kapa.ai (YC S23)
View Projectemail-marketing-campaign-optimization-using-ML
April 16, 2025 – April 17, 2025
Machine learning solution to optimize email marketing campaigns through predictive modeling. Analyzes user engagement patterns to maximize click-through rates by personalizing content, timing, and targeting. Includes data analysis, feature engineering, multiple ML models, and A/B testing framework.
View ProjectFraud-Detection-In-depth-EDA
April 9, 2025 – April 9, 2025
This repo contains In-depth EDA of Fraud Transaction Detection Dataset.
View ProjectCredit-Fraud-Detection
March 12, 2025 – March 22, 2025
Machine Learning-powered fraud detection system to detect suspicious credit card transactions in real time. Implementing a scalable MLOps pipeline with AWS, Kubernetes, Prometheus, and Grafana for real-time monitoring and alerting.DVC for data versioning, MLflow & Dagshub for experiment tracking,and CI/CD for seamless model deployment.
View ProjectMLOps-Vehicle-Insurance-Predictor
January 31, 2025 – February 6, 2025
Developed a Machine Learning-powered app to predict whether a person is likely to purchase vehicle insurance. Designed and implemented an end-to-end MLOps workflow, covering data preprocessing, model training, and deployment. Leveraged MongoDB, Docker, AWS, FastAPI, and CI/CD to ensure scalability, efficiency, and seamless production deployment.
View ProjectHFT_RealTime_DataPipeline
November 6, 2024 – December 7, 2024
HFT_RealTime_DataPipeline — repository
View ProjectHouse-Price-Insight-Pipeline
September 25, 2024 – October 20, 2024
House-Price-Insight-Pipeline — repository
View ProjectCultural Fit Analysis
The candidate's portfolio shows a strong inclination towards personal projects, indicating self-motivation and a passion for learning and applying new technologies. The diversity of projects, from RAG SaaS to MLOps pipelines and fraud detection, suggests a broad interest within the data science and machine learning domain. The alignment with a 'Data Scientist' role is strong given the project focus. However, the lack of team-based or collaborative projects in the provided data limits the assessment of cultural fit in a team environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and hands-on approach to learning and implementing complex systems. The focus on end-to-end MLOps workflows suggests an understanding of operationalizing machine learning models. However, without specific behavioral or psychometric test results, a detailed assessment of soft skills and operational fit is limited.