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Software Engineer with 1+ years in Java Backend and Data Science.
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Final-year ECE graduate from SRM IST with hands-on Java backend development experience at Saksoft Limited using Spring Boot, REST APIs, and PostgreSQL. Built ML-based prediction systems and weather forecasting tools using Python, Scikit-learn, and Pandas. Seeking a Software Engineering role to apply backend and data science skills to solve real-world problems at scale.
SRM Institute of Science and Technology, Kattankulathur
B.Tech · Electronics and Communication Engineering
August 1, 2022 – June 30, 2026
Velammal Vidhyashram, Chennai
Class XII · MPC
June 1, 2020 – May 31, 2022
Boaz Public School, Chennai
Class X
June 1, 2018 – May 31, 2020
Saksoft Limited
Java Backend Development Intern
January 1, 2025 – Present
Chennai, Tamil Nadu, India
Autism Detection using Artificial Intelligence and Machine Learning
January 1, 2024 – June 1, 2026
Designed and developed an AI/ML-based autism prediction system — performed end-to-end data cleaning, preprocessing, and exploratory data analysis on a clinical dataset of 1,000+ records to prepare it for model training. Implemented and compared multiple classification models achieving 92% accuracy on the test set — demonstrating strong potential to assist clinicians in early-stage autism screening. Analyzed performance metrics (precision, recall, F1-score) across models to select the best-performing classifier, producing a reproducible and interpretable ML pipeline using Scikit-learn.
Java Backend Power Outage Logger
January 1, 2023 – June 1, 2026
Designed and developed a Java CLI application for logging and retrieving power outage records for 50+ localities, leveraging OOP principles, Collections Framework, and file-based data persistence. Implemented structured report generation and efficient data retrieval mechanisms, reducing manual record-keeping effort by an estimated 60% compared to spreadsheet-based tracking. Strengthened core Java skills in exception handling, data structures, and modular software design — applying enterprise-style OOP patterns to a real operational use case.
Weather Prediction for Precision Farming
January 1, 2023 – June 1, 2026
Built a weather forecasting application to assist farmers in data-driven agricultural decisions — conducted feature engineering and exploratory data analysis on multi-year historical weather datasets to improve predictive signal quality. Implemented predictive ML models achieving 88% forecast accuracy on validation data, generating actionable insights for irrigation scheduling, crop management, and resource allocation across 3 crop types. Translated model outputs into a structured reporting format, enabling farmers with no ML background to act on forecasts — bridging the gap between data science and agricultural decision-making.
Artificial Intelligence: Concepts and Techniques
NPTEL
January 1, 2024 – Present
Computer Architecture
NPTEL
January 1, 2024 – Present
C and Python Programming Certification
G-Tec Computer Education, Chennai
January 1, 2023 – Present
Java, Python and Full Stack Development Courses
Udemy
January 1, 2023 – Present
AICTE Embedded Developer Internship Certificate
AICTE
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's project diversity, spanning both Java backend development and AI/ML applications, indicates a broad technical interest and adaptability. Their academic projects show initiative and a desire to apply technical skills to solve real-world problems. The internship experience aligns well with a Software Engineer role, demonstrating practical application of learned skills in a professional setting. The certifications further highlight a proactive approach to learning and skill development.
Soft Skills & Operational Fit
The candidate demonstrates good problem-solving skills through their project work, particularly in designing ML systems and backend applications. Their experience in an Agile sprint workflow suggests an ability to adapt to structured development processes and collaborate within a team. The detailed project descriptions indicate a methodical approach to development and an understanding of operational considerations like data retrieval latency and test coverage.