Experience

Built a strong technical foundation combining software development with hardware engineering principles. Gained proficiency in frontend fundamentals, building responsive layouts using HTML5, CSS3, and JavaScript. Designed and programmed microcontroller-based robots using Arduino (C++), consistently participating in technical workshops Developed technical drafting skills using AutoCAD, gaining early exposure to industry-standard engineering software.

Completed a comprehensive engineering curriculum that bridged the gap between low-level hardware design and high-level software systems.

Core programming paradigms through C, Java, and Data Structures & Algorithms, applying them to complex system design challenges.

Gained deep insight into computer architecture, from digital logic design to hardware description languages like Verilog and FPGA programming.

Explored modern fields such as Machine Learning, integrating statistical models with engineering problem-solving.

Developed full-stack proficiency by interfacing software logic with hardware components in embedded systems projects.

Collaborated with the Engineering team to improve an automated content moderation and spam/abuse detection bot, increasing classification accuracy through iterative model training and evaluation cycles.

preprocessed thousands of text and image records using Pandas and NumPy, building high-quality labeled datasets for NLP-based classification models.

Trained and evaluated NLP text classification models to detect inappropriate user behavior, spam, and abusive content, iterating on feature engineering and hyperparameter tuning to reduce false positives.

Built data visualization dashboards using Matplotlib to communicate model performance metrics, dataset distributions, and edge-case patterns to the Engineering team.

Identified edge cases in user behavior that were bypassing existing filters, providing critical feedback to engineering for model retuning and improved detection coverage.

Manage and optimize multi-cloud infrastructure across AWS and Azure for a 50-person team, ensuring high availability, security compliance, and seamless day-to-day operations.

Provision, configure, and maintain cloud compute instances (AWS EC2, Azure VMs) across Windows environments to support development and production workloads.

Administer AWS IAM users, roles, and policies to enforce security best practices and least-privilege access.

Implement Infrastructure as Code (IaC) using Terraform to automate resource provisioning and maintain reproducible cloud environments.

Monitor cloud resource utilization and health metrics to ensure optimal performance and cost-efficiency.

Troubleshoot connectivity (RDP/SSH), VPN, and network performance issues, significantly reducing downtime for distributed remote teams.