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@ -155,15 +155,6 @@ AI Systems Engineer with expertise intersecting machine learning optimization, r
\textbf{Tech Stacks: } & PyTorch; Stable-Baselines3; ROS2; Arduino IDE; React; FastAPI; Flask; Jest; PyTest; Docker; Jenkins; Terraform; AWS (EC2, S3); Nginx Proxy Manager; Cloudflare; Prometheus; Grafana; SQLite; PostgreSQL \\
\end{tabularx}
\vspace{-10pt}
% %-----------SKILLS-----------
% \section{\color{blue}SKILLS \& TECHSTACKS}
% \begin{tabularx}{\textwidth}{ @{} >{\bfseries}l X }
% % \textbf{Certifications: } & AWS Solutions Architect\\
% \textbf{Skills: } & AI; DevOps; Cloud Computing; IaC; Containerization; CI/CD; Monitoring; Data Engineering; ML Ops \\
% \textbf{Languages: } & Python; C++; C; JavaScript; Rust; HTML; Java; Bash \\
% \textbf{Tech Stacks: } & FastAPI; PyTorch; React; Flask; SQLite; PostgresSQL; NumPy; SciPy; Scikit-learn; Matplotlib; MongoDB; Docker; Git; Jenkins; Terraform; AWS; Kubernetes; Express JS; Node.js; Swagger \\
% \end{tabularx}
% \vspace{-10pt}
%----------Experience----------
\section{\color{blue}WORK EXPERIENCE}
@ -217,26 +208,6 @@ AI Systems Engineer with expertise intersecting machine learning optimization, r
\resumeSubHeadingListEnd
\vspace{-7pt}
% %-----------PROJECTS-----------
% \section{\color{blue}PROJECTS}
% \resumeSubHeadingListStart
%
% \resumeProjectHeading {\textbf{\color{black}Home lab Adminstration} $|$ \color{blue} \emph{Docker, Terraform, Jenkins, Prometheus, Grafana, SSL/TLS}}{}
% \resumeItemListStart
% \resumeItem{Orchestrate a comprehensive home lab environment managing 15+ Docker containers for media, web, and gaming services, configured auto-renewal SSL/TLS certification with Let’s Encrypt, setup Prometheus/Grafana monitoring, and applied Fail2Ban for robust security achieving 99.9\% uptime and detailed system analytics}
% \resumeItemListEnd
%
% \resumeProjectHeading{\textbf{\color{black}Heart Disease Predictor} $|$ \color{blue} \emph{Python, Flask, RESTful, HTML, CSS, JS}}{}
% \resumeItemListStart
% \resumeItem{Developed a scalable Flask-RESTful API paired with an interactive HTML/JS frontend while leveraging the UCI dataset and implemented real-time feature scaling with hyperparameter tuning to deliver a 95\% prediction accuracy, supporting timely clinical decision-making}
% \resumeItemListEnd
%
% \resumeProjectHeading{\textbf{\color{black} Real-Time Noise Cancellation with RL} $|$ \color{blue} \emph{Python, PyTorch, Gymnasium, SciPy, librosa}}{}
% \resumeItemListStart
% \resumeItem{Created a bespoke OpenAI Gym environment incorporating FFT-based audio processing and trained a PPO agent to perform adaptive noise cancellation in real time, achieving processing speeds exceeding 5,200 FPS for high-fidelity audio performance}
% \resumeItemListEnd
% \resumeSubHeadingListEnd
% \vspace{-7pt}
\section{\color{blue}PUBLICATIONS}
\resumeSubHeadingListStart