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c6e3b6df5d Update CI
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Build and Release PDF / release (push) Successful in 2m46s
Signed-off-by: Nikolaos Karaolidis <nick@karaolidis.com>
2025-07-31 15:35:55 +01:00
2 changed files with 15 additions and 16 deletions

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@@ -31,7 +31,6 @@ jobs:
- name: Release
uses: https://github.com/akkuman/gitea-release-action@main
with:
name: "Release ${{github.sha}}"
tag_name: "release-${{github.sha}}"
files: |-
main.pdf

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@@ -1,18 +1,3 @@
\datedlocatedsubsection{Nov 2024 - Present}
{SAS Institute, Glasgow, UK}
{Senior Associate Software Developer}
{%
A global leader in analytics and AI software, SAS is empowering organizations across more than 145 countries.
%
\begin{itemize}
\item Spearheaded the design and development of a microservices-based platform (\textbf{Go}, \textbf{Python}, \textbf{Postgres}, \textbf{Redis}), enabling massively parallel task execution at accelerated rates compared to the legacy solution.
\item Architected distributed task scheduling with \textbf{Ray} and \textbf{KEDA}-powered autoscaling on \textbf{Kubernetes} clusters.
\item Authored and maintained the platform's \textbf{unit test} suite and \textbf{CI/CD} pipelines to guarantee reliability across all services.
\item Triaged and fixed Viya 4 UI (\textbf{TypeScript}) and backend (\textbf{Go}/\textbf{Java}) issues.
\item Prototyped a lightweight isolation platform for the SAS language executor using \textbf{Linux kernel} capabilities and system calls.
\end{itemize}
}
\datedlocatedsubsection{Jun 2023 - Sep 2023}
{WebHotelier | primalRES, Athens, Greece}
{Software Engineering Intern}
@@ -44,3 +29,18 @@
\item Authored clean and maintainable code which was tested using unit, integration, and end-to-end testing.
\end{itemize}
}
\datedlocatedsubsection{Jul 2019}
{InterSearch Worldwide, Dubai, UAE}
{Intern}
{%
Ranked among the 30 largest executive search firms in the world, InterSearch Worldwide has 90 offices in 50 different countries.
%
\begin{itemize}
\item Developed a \textbf{Python} CLI Tool to automate Candidate CV and Financial Documentation Entry, extracting information from .pdf, .doc, and .docx CVs to a \textbf{FileFinder} database.
\item Incorporated \textbf{XML} parsing techniques for data extraction from Microsoft Word documents, and \textbf{Optical Character Recognition} with OpenCV to interpret non-editable PDFs.
\item Applied \textbf{Natural Language Processing} using NLTK to categorize text tokens such as names, addresses, and skills.
\item Navigated database interactions using PyAutoGUI, a workaround due to limited direct database access.
\item Refined the E-mail spam filter to improve productivity and internal communications.
\end{itemize}
}