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AI/ML Engineer with 1+ years in Quantitative Modeling & Software Development
Computer Science Engineering graduate specializing in Artificial Intelligence and Machine Learning, with hands-on experience building quantitative models, risk analytics pipelines, and AI-powered applications. Proficient in Python (Pandas, NumPy, Scikit-learn) and object-oriented software development, with practical exposure to statistical modeling, Monte Carlo simulation, and machine learning frameworks including TensorFlow and PyTorch. Experienced in designing and consuming RESTful APIs, working with large datasets, and developing end-to-end solutions spanning model implementation, backtesting logic, and performance optimization. Demonstrated ability to collaborate cross-functionally, conduct peer code reviews, and deliver robust, well-documented software. Passionate about applying data science and software engineering to solve complex analytical and forecasting challenges in high-stakes environments.
Christ (Deemed To Be University)
B.Tech · Computer Science & Engineering (AI & ML)
August 1, 2022 – June 30, 2026
Mar Ivanios Bethany Senior Secondary School
Class XII
N/A – May 31, 2022
Tech Mahindra Limited
Trainee - Embedded AI/ML Engineer
January 1, 2026 – April 1, 2026
Bengaluru, Karnataka, India
MariApps Marine Solutions Pvt. Ltd
Web Development Intern
May 1, 2025 – June 1, 2025
Cochin, Kerala, India
Apar Peopleworld Technologies Pvt. Ltd
Web Development Intern
April 1, 2024 – May 1, 2024
Bengaluru, Karnataka, India
Self-Healing AI Firewall - Real-Time Threat Detection & Forecasting Dashboard
June 19, 2026 – Present
Trained a CNN/ML-based classifier on CICIDS-2017 dataset to detect malicious network traffic; implemented adaptive RL-based threshold tuning - demonstrating quantitative model design, training, backtesting logic, and performance optimization. Built a real-time Streamlit monitoring dashboard for live traffic visualization and anomaly alerts with XAI-style visual explanations, enabling interpretable model output for non-technical stakeholders.
Customer Churn Analysis - Statistical Risk Modeling Dashboard
June 19, 2026 – Present
Developed a statistical analytics solution using Power BI to analyze telecom churn patterns; calculated KPIs including churn rate (~26%) and identified high-risk customer segments through quantitative segmentation. Applied exploratory data analysis (EDA) techniques using Pandas and NumPy to process large datasets and derive actionable risk indicators.
Unified System for Handwritten & Printed Bill Digitisation
June 19, 2026 – Present
Built an end-to-end computer vision pipeline for document digitization: image preprocessing (noise reduction, normalization, resizing), layout parsing, and key-value extraction using OpenCV and Microsoft TrOCR. Achieved ~70% reduction in manual data-entry time; integrated FastAPI backend and SQL database for structured data storage, retrieval, and API-driven access.
Sports Attendance Tracker
June 19, 2026 – Present
Developed a real-time web-based system for 200+ participants with session-based tracking and CRUD REST API endpoints, demonstrating RESTful API design and large dataset management.
Data Visualisation: Empowering Business with Effective Insights
TATA
June 1, 2026 – Present
Claude with Google Vertex AI
Anthropic
June 1, 2026 – Present
Introducing SAP Business Data Cloud
SAP
June 1, 2026 – Present
Claude with Amazon Bedrock
Anthropic
June 1, 2026 – Present
MATLAB Certified
MathWorks
June 1, 2026 – Present
Data Analytics & Job Simulation
Deloitte
June 1, 2026 – Present
Introduction to Data Science
Simplilearn
June 1, 2026 – Present
Cloud Computing on AWS
Udemy
June 1, 2026 – Present
Full Stack Development
Simplilearn
June 1, 2026 – Present
Enhancing Soft Skills & Personality
NPTEL
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from network security to customer churn analysis and document digitization, demonstrates adaptability and a broad interest in applying AI/ML across different domains. The academic background in Computer Science & Engineering (AI & ML) aligns well with the target role. The various certifications, including those in cloud computing and data analytics, indicate a continuous learning mindset. While the projects are personal, they showcase initiative and a drive to build practical solutions. The web development internships, though not directly AI/ML, show a breadth of software engineering exposure.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experiences indicate an ability to collaborate with cross-functional teams, conduct peer code reviews, and deliver documented technical outputs. The 'Enhancing Soft Skills & Personality' certification and participation in inter-college tournaments suggest a proactive approach to personal development and teamwork. The focus on interpretable model output for non-technical stakeholders in the 'Self-Healing AI Firewall' project highlights an understanding of communication beyond technical peers.