diff --git a/coverletters/cl.pdf b/coverletters/cl.pdf index 2efaefa..d64b87a 100644 Binary files a/coverletters/cl.pdf and b/coverletters/cl.pdf differ diff --git a/coverletters/cl.tex b/coverletters/cl.tex index 5b55fad..3886b18 100644 --- a/coverletters/cl.tex +++ b/coverletters/cl.tex @@ -6,10 +6,10 @@ % Define variables %% Job related -\newcommand{\companyName}{Devopie Inc.} +\newcommand{\companyName}{DataAnnotation} \newcommand{\hiringManager}{Hiring Team} -\newcommand{\companyAddress}{Hamilton, ON} -\newcommand{\position}{Backend Developer} +\newcommand{\companyAddress}{Kitchener, ON} +\newcommand{\position}{Cloud Engineer - AI Trainer} %% Personal \newcommand{\name}{Murtadha Nisyif} @@ -49,14 +49,10 @@ I’m eager to contribute my skills and energy to a team committed to technical % MAIN BODY SECTION %============================= \vspace{1em} -\noindent My experience in software engineering at the University of Guelph has honed my skills in writing high-performance, scalable code in C and Python. I have worked on real-time systems for robotics applications and deployed machine learning models on hardware-accelerated SoCs (Xilinx Kria). These projects strengthened my understanding of system reliability, latency sensitivity, and performance tuning. +\noindent My technical experience includes training ML models, deploying microservices, and integrating code into automated testing workflows. I’ve developed a heart disease prediction app using Flask and scikit-learn, engineered full-stack projects with React and Java, and maintained a Docker-based homelab environment running CI/CD and container orchestration. Other projects include memory allocation simulators in C, car classification using CNNs, reinforcement-based dynamic noise cancellation, and an accessibility-focused Braille converter powered by Raspberry Pi. \vspace{1em} -At the Robotics Institute, I developed and deployed a backend system with Node.js and PostgresDB for an accessibility-focused application. Hosted on AWS EC2, the system featured a web frontend that enabled real-time user activity monitoring and analytics. I maintained the entire stack, ensuring dependency updates, feedback integration, and security hardening. This hands-on work gave me direct experience with cloud infrastructure, devops tools, and end-to-end application management. - -\vspace{1em} -In addition, I manage a personal homelab where I design, test, and monitor containerized services using Docker and Jenkins CI/CD pipelines. This setup has allowed me to explore concepts like automated testing, rollback strategies, and deployment resilience knowledge I continuously apply to side projects like ML inference APIs, Flask applications, and object storage management. - +In addition to my programming work, I bring strong written communication skills and attention to detail. Whether writing technical documentation, explaining model decisions, or debugging tricky outputs, I enjoy breaking down complex problems and analyzing code quality. I am confident in evaluating code for correctness, performance, and clarity. I look forward to helping shape models that do the same. %============================= % CLOSING SECTION diff --git a/resumes/Murtadha.pdf b/resumes/Murtadha.pdf index 3e4f640..1ceb0f6 100644 Binary files a/resumes/Murtadha.pdf and b/resumes/Murtadha.pdf differ diff --git a/resumes/Murtadha.tex b/resumes/Murtadha.tex index a9336ff..ea1dcca 100644 --- a/resumes/Murtadha.tex +++ b/resumes/Murtadha.tex @@ -117,13 +117,9 @@ \end{tabular*} \vspace{-10pt} -%----------Highlights---------- -\section{\color{blue}Highlights} - \resumeItemListStart - \resumeItem {Developed a Flask web app to predict heart disease using ML models, including feature encoding, scaling, and real-time prediction}\vspace{-5pt} - \resumeItem {Designed nested MongoDB schemas using Mongoose to support flexible, multi-representation document structures}\vspace{-5pt} - \resumeItem {Dockerized and deployed backend/frontend using Jenkins CI/CD with rollback capability and uptime focus}\vspace{-5pt} - \resumeItemListEnd +%----------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---------- @@ -164,24 +160,24 @@ %-----------SKILLS----------- \section{\color{blue}Skills} \begin{tabular}{ @{} >{\bfseries}l @{\hspace{1.2ex}}l} - \textbf{Languages:} & Python, C++, JavaScript, SQL, Bash \\ - \textbf{Frameworks:} & Flask, React, Node.js, ROS, Express.js \\ - \textbf{Databases:} & MongoDB (Mongoose), PostgreSQL, SQLite \\ - \textbf{DevOps:} & Docker, Jenkins, Git, Terraform, AWS \\ - \textbf{Tools:} & GitHub, Postman, Swagger, Nginx, iperf3 \\ + \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} - \resumeSubHeadingListStart - \resumeSubItem{\textbf{\color{black}Heart Condition Prediction Web App}} - {Built a Flask-based app to predict heart disease risk using ML models with real-time input processing, encoding, and instant output.} - \resumeSubItem{\textbf{\color{black}Full-stack Portfolio Project}} - {Dockerized frontend/backend using React and Java; deployed using Jenkins pipeline with AWS S3 for static hosting and MinIO for object storage.} - \resumeSubItem{\textbf{\color{black}DevOps Homelab}} - {Maintained home lab infrastructure with Docker, Kubernetes, Ceph, and Jenkins. Built versioned CI/CD pipelines for staging + rollback experiments.} - \resumeSubHeadingListEnd + \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-----------