Zain Jadoon

AI Intern

APP IN SNAP • Temps partiel

Dec 2025 - Sep 2026 • 9 mos

Worked remotely as part of the AI department, contributing to AI/ML development and research tasks. Applied machine learning concepts to practical problems involving data processing, model development, experimentation, and evaluation. Worked with Python and modern AI/ML technologies while gaining experience in developing, testing, and improving AI-driven solutions. Collaborated remotely with the team to investigate technical problems, experiment with different approaches, and deliver solutions according to project requirements. * Gained hands-on experience working in a professional AI/ML development environment. * Contributed to AI/ML experiments, model development, and evaluation. * Applied Python and machine learning techniques to practical project requirements. * Worked remotely with an AI-focused team and followed a professional development workflow. * Strengthened practical experience in data preprocessing, model experimentation, and AI solution development. * Translated academic machine-learning knowledge into real-world AI development tasks.

AI Engineer

DTC Force • Temps partiel

Apr 2025 - Dec 2025 • 8 mos

Worked on practical AI/ML and IT monitoring projects involving machine learning, Linux-based environments, network monitoring, and security operations. Contributed to data preprocessing and log analysis workflows, including cleaning operational data and preparing datasets for machine learning applications. Worked with monitoring and security tools such as Zabbix and Wazuh, analyzed system and agent activity, and contributed to usage and downtime monitoring. Developed machine learning approaches for predicting potential system failures and generating early safety-critical alerts. Collaborated with technical teams to investigate operational data, identify patterns, and translate monitoring data into actionable insights for improving system reliability. * Applied machine learning to real-world operational and monitoring data rather than purely academic datasets. * Worked with Linux, Zabbix, Wazuh, NOC monitoring, and SIEM-related workflows. * Contributed to log preprocessing and data cleaning pipelines for ML-based analysis. * Developed predictive approaches for downtime and potential system failures, supporting proactive monitoring. * Worked on agent tracking and usage monitoring to improve visibility into system activity. * Gained hands-on experience combining AI/ML with cloud/IT infrastructure and cybersecurity monitoring. * Worked in a professional technical environment involving real operational data and system-monitoring requirements.