•I am an AI/ML Engineer with a passion for building scalable, AI-driven solutions that drive efficiency, optimize costs, and enhance decision-making. With expertise in machine learning, cloud computing, and IoT, I specialize in AI model selection, predictive maintenance, and cloud cost/environmental impact analysis.
š¹ Current Role: Associate AI/ML Engineer at Compunnel Inc.
AI-Driven Model Selection System: Developed using CrewAI & Azure, integrating multiple AI agents for automated model recommendations, compliance checks, and data assessment.
Cloud Cost & Environmental Impact Analysis: Optimizing FinOps strategies, tracking PUE and emissions, reducing cloud expenditure and carbon footprint.
š¹ Key Projects & Expertise:
IoT-Based Predictive Maintenance: Engineered real-time monitoring solutions using STM32 sensors & Raspberry Pi, visualized insights via Power BI.
MLOps-Based Predictive Analytics: Developed AWS-hosted predictive maintenance models using Isolation Forest, Linear Regression.
AI for Cloud Optimization: Built anomaly detection systems in Databricks & Azure to optimize cloud usage.
Car Rental Demand Prediction & E-commerce Analytics: Forecasting demand trends through machine learning.
š¹ Technical Stack:
Python | SQL | Azure | AWS | Databricks | CrewAI | TensorFlow | PyTorch | Power BI | IoT Sensors (STM32, Raspberry Pi)
š Recognitions & Certifications:
š "Shining Star" Award for outstanding performance
š Microsoft Azure Data Scientist Associate (DP-100) ( Coursera)
š Google Data Analytics Certificate (Coursera)
I thrive at the intersection of AI, cloud computing, and IoT, and Iām always eager to explore innovative solutions that make AI more efficient, cost-effective, and impactful.
