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AI Engineer with 1+ years in Machine Learning & Data Science
Demonstrated strong foundation in Data Science with hands-on experience in Machine Learning, Deep Learning, and predictive analytics through academic projects and internships. Developed AI-based applications including a safe route prediction system and an accident detection model with real-time alert mechanisms. Applied data preprocessing, feature engineering, and model optimization techniques to improve model accuracy and performance. Proficient in Python and R, with practical exposure to libraries such as Pandas, NumPy, Scikit-learn, and OpenCV for data analysis and model development. Experienced in handling structured and unstructured datasets, extracting meaningful insights to support data-driven decision-making.
Bishop Heber College, Tiruchirappalli
Master of Science · Data Science
August 1, 2024 – June 30, 2026
Dr. NGP Arts and Science College, Coimbatore
Bachelor of Science · Computer Science
August 1, 2021 – June 30, 2024
Cheran Matric Higher Secondary School
HSC
N/A – May 31, 2021
Cheran Matric Higher Secondary School
SSLC
N/A – May 31, 2019
CodTech IT Solutions
Data Science Intern
May 1, 2025 – Present
India
Cognifyz Technologies
Machine Learning Intern
December 1, 2024 – December 1, 2024
India
AI-Based Safe Path Predictor Application
June 1, 2026 – Present
Developing an AI-driven route optimization system that prioritizes safety using real-time and historical data analysis. Implementing machine learning models to identify accident-prone zones and predict route safety scores. Integrating traffic density, road conditions, and environmental factors for accurate risk assessment. Utilizing Python and mapping APIs to enable route visualization and dynamic navigation updates. Designing a user-focused solution that helps commuters choose safer routes over shorter or faster alternatives. Performing data preprocessing and predictive analytics for model training.
AI-Based Accident Detection and Emergency Alert System
June 1, 2026 – Present
Built a real-time accident detection system using YOLOv8 and OpenCV. Processed live video streams for collision and abnormal vehicle behavior detection. Automated emergency alerts with location details and Google Maps integration. Developed a Streamlit-based monitoring interface for detection management. Applied computer vision techniques for high-accuracy event recognition. Worked on real-time processing pipelines for smart traffic applications. Integrated alert mechanisms to improve emergency response efficiency. Conducted testing and optimization for detection performance.
View ProjectPython Programming Certification
Unknown
June 1, 2026 – Present
Diploma in Computer Application
Unknown
June 1, 2026 – Present
Certification in Basics of Data Science
Unknown
June 1, 2026 – Present
Java Course Certification
Unknown
June 1, 2026 – Present
Certification in Cloud Computing
Unknown
June 1, 2026 – Present
Developed AI-based projects in computer vision and predictive analytics
Unknown
June 1, 2026 – Present
Built real-time AI applications using YOLOv8, OpenCV, and Streamlit
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internships show a strong alignment with the target role of an AI Engineer, focusing on practical applications of machine learning, deep learning, and computer vision. The diversity in projects (route optimization, accident detection) indicates a broad interest within AI. The listed skills and technologies are highly relevant to modern AI development, suggesting a good cultural fit for a technically driven AI team. The pursuit of a Master's in Data Science further reinforces a commitment to the field. However, the lack of non-academic or open-source contributions limits the assessment of broader collaborative or community engagement aspects of cultural fit.
Soft Skills & Operational Fit
The candidate demonstrates a proactive approach to learning and applying AI/ML concepts through academic projects and internships. Their focus on real-time applications and end-to-end data pipelines suggests an operational fit for roles requiring practical implementation and deployment. The descriptions indicate an ability to work with diverse datasets and apply analytical thinking, which are valuable for problem-solving in an AI engineering context. However, without direct assessment data on communication, logical reasoning, or teamwork, a comprehensive evaluation of soft skills and operational fit is limited.