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job: apply some changes to apply to Pythian

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coverletters/cl.tex
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% Define variables
%% Job related
\newcommand{\companyName}{DataAnnotation}
\newcommand{\companyName}{Pythian}
\newcommand{\hiringManager}{Hiring Team}
\newcommand{\companyAddress}{Kitchener, ON}
\newcommand{\position}{Cloud Engineer - AI Trainer}
\newcommand{\companyAddress}{Remote, Canada}
\newcommand{\position}{AI/ML Engineer}
%% Personal
\newcommand{\name}{Murtadha Nisyif}
@ -40,25 +40,34 @@
%=============================
% OPENING SECTION
%=============================
I am writing to express my interest in the \position{} role at \companyName.
I am a recent graduate in Computer Engineering with a background in backend development, cloud deployment, and machine learning systems.
I have built and deployed full-stack applications and production-level services using Python, Docker, Flask, and CI/CD pipelines, and have experience working in both academic and team-based engineering environments.
I’m eager to contribute my skills and energy to a team committed to technical excellence and innovation.
Pythian’s reputation for solving "tough data challenges" resonates deeply with my background in engineering high-efficiency AI pipelines for congested network environments.
As a Computer Engineering Graduate and Researcher specialized in Semantic Communications and Edge Computing, I have spent my career ensuring that mission-critical data remains reliable and performant—the same standard Pythian has championed since 1997.
I am eager to bring my expertise in model optimization and MLOps to the \position{} role to help your clients leverage bleeding-edge technologies.
%=============================
% MAIN BODY SECTION
%=============================
\vspace{1em}
\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.
\noindent My technical background aligns directly with Pythian’s focus on robust, scalable AI systems:
\begin{itemize}[leftmargin=1.5em, labelsep=0.5em]
\item \textbf{Optimized AI Pipelines:} I developed semantic communication pipelines using Swin Transformer models that achieved a 30x reduction in bandwidth and 29\% lower latency while maintaining 96\% task accuracy.
\item \textbf{Production-Ready Deployment:} I have extensive experience containerizing multi-technology stacks with Docker and ROS2, and automating cloud infrastructure (AWS) using Terraform.
\item \textbf{MLOps \& Scalability:} I implemented CI/CD pipelines via Jenkins and GitLab, reducing manual deployment steps by 80\%, and orchestrated a home lab environment managing 15+ Docker containers with Prometheus/Grafana monitoring.
\item \textbf{Advanced AI Research:} I have published first-author IEEE research on adaptive JSCC frameworks and network-aware image transmission, demonstrating my ability to stay at the forefront of transformer-based architectures.
\end{itemize}
\vspace{1em}
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.
Pythian’s commitment to digital transformation and operational excellence mirrors my own drive to bridge the gap between complex model prototypes and production-ready AI systems.
Whether it is quantizing models for edge constraints or orchestrating global cloud infrastructure, I thrive on making AI both accessible and highly efficient.
%=============================
% CLOSING SECTION
%=============================
\vspace{1em}
\noindent I am confident that my hands-on experience, collaborative mindset, and drive for technical excellence make me a strong fit for the \position{} role at \companyName. I am available for an interview at your convenience and would appreciate the opportunity to further discuss how I can contribute to your team. Please feel free to reach out to me at \email{} or by phone at \phone. Thank you for your time and consideration.
\noindent I am confident that my blend of research-driven innovation and hands-on DevOps experience will allow me to contribute immediately to Pythian’s AI initiatives.
I look forward to the opportunity to discuss how my background in high-performance ML engineering can support your clients’ data goals.
Thank you for your time and consideration.
\vspace{2em}
\noindent Sincerely, \\

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resumes/mnisyif_resume.tex
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\begin{tabular*}{\textwidth}{@{\hspace{-1ex}}l}
\textbf{\href{http://m.nisyif.com/}{\Huge\color{blue}MURTADHA NISYIF}} \vspace{2pt}\\
\href{mailto:mnisyif@gmail.com}{\faIcon{at} mnisyif@gmail.com} $|$
\faIcon{phone-square-alt} +964 775 608 4424 $|$
\faIcon{map-marker-alt} Karbala, Iraq $|$
\faIcon{phone-square-alt} +1 (519) 502-8463 $|$
\faIcon{map-marker-alt} Kitchener, Ontario $|$
\href{https://m.nisyif.com/}{\faIcon{user-tie} m.nisyif.com} $|$
\href{https://www.linkedin.com/in/mnisyif}{\faIcon{linkedin} linkedin.com/ln/mnisyif} $|$
\href{https://github.com/mnisyif}{\faIcon{github} github.com/mnisyif}\vspace{12pt} \\
@ -135,7 +135,7 @@
%-----------SUMMARY----------
\section{\color{blue}SUMMARY}
Versatile Computer Engineer and Researcher specialized in Semantic Communications and Edge Computing. First author of two IEEE conference papers focused on optimizing edge-cloud communication through task-driven feature extraction. \textbf{Bilingual in English and Arabic}, with expertise in developing high-efficiency AI pipelines for 5G/6G and Smart City infrastructure. Proven track record of reducing bandwidth demand by \textbf{30$\times$} while maintaining 96\% task accuracy in congested network environments
Versatile Computer Engineer and Researcher specialized in Semantic Communications and Edge Computing. First author of two IEEE conference papers focused on optimizing edge-cloud communication through task-driven feature extraction, with expertise in developing high-efficiency AI pipelines for 5G/6G networks. Proven track record of reducing bandwidth demand by \textbf{30$\times$} while maintaining 96\% task accuracy in congested network environments
\vspace{-7pt}
@ -223,7 +223,7 @@ Versatile Computer Engineer and Researcher specialized in Semantic Communication
\resumeProjectHeading
{\textbf{Network-Aware Adaptive Semantic Image Transmission in Edge-Cloud Communications}}{MECOM 2025}
\resumeItemListStart
\resumeItem{Proposed an adaptive JSCC framework that couples Swin-Transformers with real-time network telemetry to optimize image transmission over dynamic 5G/6G core networks (Accepted, IEEE MECOM25)}
\resumeItem{Proposed an adaptive JSCC framework that couples Swin-Transformers with real-time network telemetry to optimize image transmission over dynamic 5G/6G core networks (Published, IEEE Xplore)}
\resumeItemListEnd
\resumeProjectHeading