AI Engineer with 1+ years in Data Science & Machine Learning
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AI Product Developer skilled in Data Science, Machine Learning, and Intelligent Automation, specializing in building scalable AI-driven solutions and conversational agents, voice AI systems. Experienced in AWS Bedrock and FastAPI microservices to create impactful, real-world AI applications
MVJ College Of Engineering, VTU
B.E. · Computer Science Engineering - Data Science
August 1, 2021 – June 30, 2025
Mahesh PU College
Pre-University · PCMB
June 1, 2019 – May 31, 2021
Adarsha Vidyalaya (RMSA)
SSLC
June 1, 2018 – May 31, 2019
Rooman Technologies Pvt. Ltd.
AI Product Developer
September 1, 2025 – Present
Bengaluru, Karnataka, India
Pheuna Technologies
AI Data Quality Analyst Intern
September 1, 2024 – February 1, 2025
Bengaluru, Karnataka, India
Pheuna Technologies
Data Analyst Intern
October 1, 2023 – November 1, 2023
Bengaluru, Karnataka, India
Forest fire detection
June 25, 2026 – Present
The system is designed to process live video feeds from cameras, identifying potential fire outbreaks with high accuracy. The CNN model was trained on a diverse dataset of fire and non-fire images, ensuring robust performance across various conditions. The project also integrates a user-friendly interface for real-time monitoring and Email alerts.
Fraud Transaction Classification
June 25, 2026 – Present
Classifying whether a particular transaction is fraudulent or not. Performed feature engineering, handling of missing data, handling imbalanced datasets, hyperparameter optimization, checking correlations, feature selection. Performed Cross validations.
Serverless Agentic Workflows with Amazon Bedrock
deeplearning.ai
June 1, 2026 – Present
Machine Learning Specialization
Great Learning
June 1, 2026 – Present
AWS Certified Cloud Practitioner
AWS
June 1, 2026 – Present
Claude Certified Architect – Foundation
CCA-F
June 1, 2026 – Present
Building AI Voice Agents for Production
deeplearning.ai
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic background in Computer Science Engineering - Data Science, coupled with practical project experience and certifications, indicates a strong interest and commitment to the AI domain. The diversity of projects (computer vision, tabular data classification, voice AI platforms) suggests adaptability and a broad skill set. The involvement in team lead roles also points to a collaborative mindset.
Soft Skills & Operational Fit
The candidate demonstrates leadership potential through involvement as a Team Lead in academic initiatives. The project descriptions indicate an ability to work on complex problems and deliver functional solutions. The experience as an AI Product Developer suggests an understanding of product development lifecycle and impact measurement (e.g., ~30% improvement in learner engagement).