Linux System Engineer

Administered and maintained 30–50+ Linux-based Ubuntu and CentOS desktop systems supporting secure Optical Mark Recognition scanning operations across more than six examination cycles. Performed system updates, patch management, process monitoring, service monitoring, and hardware support to maintain uptime and security compliance.

Managed user accounts, file permissions, and SSH-based remote access for 30–50+ users while protecting confidential examination data with zero reported security incidents. Diagnosed DNS, connectivity, and hardware issues, reducing average incident resolution time by 40–50%, and documented setup and troubleshooting procedures for support staff onboarding.

Collected, cleaned, and preprocessed structured datasets for predictive modeling initiatives. Conducted exploratory data analysis and feature engineering to improve data quality and model performance.

Built and evaluated classification and regression models using Python and Scikit-learn. Supported data-driven analysis through model development, validation, and interpretation of results.

Developed and trained machine learning models using Python and TensorFlow for real-world applications. Applied data preprocessing and model-building techniques to support analytical problem solving.

Used regression, classification, and clustering algorithms to solve data-driven problems. Gained practical experience with machine learning workflows and model evaluation.

CGPA: 7.58

Score: 68%

Score: 82%