job(software): update resume layout, and add more information for each project

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Murtadha 2025-06-14 16:39:24 -04:00
parent 9c831333c9
commit 7899e41093
2 changed files with 34 additions and 31 deletions

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\end{tabular*}
\vspace{-10pt}
%----------Summary----------
\section{\color{blue}Summary}
Versatile software engineer with hands-on experience in backend systems, machine learning, DevOps, and embedded platforms. Proficient in Python, C++, Rust and JS, with a portfolio of applied AI, web services, and hardware integrated projects. Passionate about writing clean, testable code and clearly communicating technical insights
\vspace{-5pt}
%----------Experience----------
\section{\color{blue}Relevant Work Experience}
\resumeSubHeadingListStart
\resumeSubheading
{Software Engineer - Machine Learning}{Jan 2024 -- Dec 2024}
{Software Engineer - Machine Learning}{Jan 2024 -- Aug 2025}
{University of Guelph}{Guelph, Ontario}
\resumeItemListStart
\resumeItem {Drove a \textbf{30$\times$ bandwidth reduction} and \textbf{29\% latency cut} by integrating Swin-Transformer semantic compression into an edge-cloud pipeline, while keeping image fidelity $\ge$88\%}
@ -156,37 +151,45 @@
\resumeItemListEnd
\resumeSubHeadingListEnd
%-----------SKILLS-----------
\section{\color{blue}Skills}
\begin{tabular}{ @{} >{\bfseries}l @{\hspace{1.2ex}}l}
\textbf{Languages:} &Python, C++, JavaScript, C, SQL, Java, C\#, Bash \\
\textbf{Frameworks:} &Flask, FastAPI, Node.js, React, TensorFlow, PyTorch, ROS2 \\
\textbf{Databases:} &MongoDB, PostgreSQL, SQLite \\
\textbf{Tools:} &Docker, Kubernetes, Git, Jenkins, Terraform, AWS, Vitis AI \\
\end{tabular}
\vspace{-8pt}
%-----------PROJECTS-----------
\section{\color{blue}Projects}
\begin{itemize}[leftmargin=0.15in, label={}]
\item \textbf{Heart Disease Predictor} Flask app with sklearn model, real-time prediction, and input feature scaling \vspace{-5pt}
\item \textbf{StonkBot} Discord bot for fantasy stock trading using Python, Matplotlib, and live API feeds \vspace{-5pt}
\item \textbf{Car Model Classifier} CNN trained on Stanford Cars dataset with ResNet/EfficientNet architectures\vspace{-5pt}
\item \textbf{Memory Allocator Simulator} C implementation of First/Best/Worst fit memory management\vspace{-5pt}
\item \textbf{Braille Converter Device} Raspberry Pi-based image-to-Braille translator for accessibility\vspace{-5pt}
\item \textbf{Clean Architecture Backend} C\# backend for portfolio website, CI/CD-ready with REST API\vspace{-5pt}
\item \textbf{RL Noise Cancelling} Real-time audio filtering using RL and sparse training (PyTorch)\vspace{-5pt}
\end{itemize}
\vspace{-10pt}
%-----------EDUCATION-----------
%-----------EDUCATION-----------
\section{\color{blue}Education}
\resumeSubHeadingListStart
\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{MASc. - Computer Engineering}}{}
\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{B.Comp. - Computer Science}}{}
\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{B.Eng. - Computer Engineering}}{}
\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{B.Eng - Comp. Engineering, B.Comp. - Comp. Science}}{}
\resumeSubHeadingListEnd
\vspace{-8pt}
%-----------SKILLS-----------
\section{\color{blue}Skills}
\begin{tabularx}{\textwidth}{ @{} >{\bfseries}l X }
\textbf{Skills:} & AI; DevOps; Software Testing; Cloud Computing; Data Analysis; ML; CI/CD \\
\textbf{Technologies: } & Python; C++; C; JavaScript; Rust; HTML; Java; Bash; Flask; FastAPI; Swagger; Node.js; React; PyTorch; MongoDB; PostgreSQL; SQLite; Docker; Kubernetes; Git; Jenkins; Terraform; AWS \\
\textbf{Languages: } & English (Fluent); Arabic (Fluent)
\end{tabularx}
\vspace{-8pt}
%-----------PROJECTS-----------
\section{\color{blue}Projects}
\resumeSubHeadingListStart
\resumeSubItem{\textbf{\color{black}Personal Portfolio Website}}
{Full-Stack Developer: built with React frontend and Rust backend, integrated end-to-end Jenkins CI/CD and Docker deployment; reduced manual deployment time by 70\%}
\resumeSubItem{\textbf{\color{black}Home lab Administration}}
{Managed a fleet of 15 Docker containers hosting media services, websites, and game servers; implemented automated Let's Encrypt SSL issuance, Prometheus/ Grafana monitoring, and Fail2Ban SSH hardening, achieving 99.9\% uptime}
\resumeSubItem{\textbf{\color{black} Heart Disease Predictor}}
{Full-stack Flask-RESTful application with HTML/CSS/JavaScript frontend; trained on the UCI Heart Disease dataset (11 clinical features) achieving 95\% accuracy; implements input feature scaling for normalized, real-time predictions}
\resumeSubItem{\textbf{\color{black}Real-Time Noise cancelling with RL}}
{Built a custom OpenAl Gym environment in Python that leverages Dynamic Sparse Training (DST) and FFT-based audio processing (librosa) to adaptively filter noise; implemented a waveform-similarity reward and achieved up to 5209 FPS during PPO training}
\resumeSubHeadingListEnd
\vspace{-8pt}
\end{document}