From 5c2b3e71c99efe7effa5033f770ee00500c424da Mon Sep 17 00:00:00 2001
From: Gustaf Rydholm <gustaf.rydholm@gmail.com>
Date: Sat, 11 Sep 2021 16:45:39 +0200
Subject: Rename files

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+\section{Experience}
+% \vspace{0.4cm}
+% According to Google Recruiters, use the XYZ formula - Accomplished [X] as measured by [Y], by doing [Z]
+
+\company{Software Engineer}
+{Nexure}
+{Aug 2021 -- present}
+{Stockholm, Sweden}
+{
+Working with backend development for payment solutions.
+\\\\
+Keywords: Kotlin, backend, SQL, Spring Boot, AWS, Kubernetes, microservices, Docker, CI/CD
+\\
+}
+\ruler
+
+\company{Machine Learning/Software Engineer}
+{Saab}
+{Oct 2020 -- Aug 2021 \qquad 10 months}
+{Stockholm, Sweden}
+{
+Worked on a cloud application for the surveillance and intelligence domain. Developed deep learning models for multi-modal sequence predictions. I also did a lot of backend engineering and data mining. 
+\\\\
+Keywords: Python, Kubernetes, Helm, Deep Learning, data mining, microservices, Kafka, Docker, CI/CD
+\\
+}
+\ruler
+
+\company{Machine Learning Engineer}
+{Saab}
+{Aug 2018 -- Oct 2020 \qquad 2 years and 2 months}
+{Stockholm, Sweden}
+{
+Researched potential use cases for machine learning within the electronic warfare domain. I also developed simulation software for complex signal environments. This simulator allowed the entire research team to investigate new ideas quicker. \\\\
+Keywords: Python, VHDL, PyToch, Digital Signal Processing
+}\\
+
+\ruler
+
+%\company{Master's Thesis}
+%{Ericsson AB}
+%{Jan 2018 -- June 2018 \qquad 6 months}
+%{Stockholm, Sweden}
+%{
+%Built a \textbf{natural language processing} system using a biologically %inspired machine learning algorithm, called \textbf{Hierarchical Temporal %Memory}, for detecting anomalies in system logs. Demonstrated that the system %was able to achieve similar performance to the existing system. Developed with %\textbf{Python}, \textbf{NuPIC}, and \textbf{pandas}.
+%}\\
+
+%\ruler
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