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author | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2021-09-11 16:45:39 +0200 |
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committer | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2021-09-11 16:45:39 +0200 |
commit | 5c2b3e71c99efe7effa5033f770ee00500c424da (patch) | |
tree | ddf0d59c8e40627e2e071f14d5ba27384ab5e58d /work.tex | |
parent | 0d50fc5d90bf85fbe0fb4017fd18afd9da4efd08 (diff) |
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diff --git a/work.tex b/work.tex deleted file mode 100644 index e46616b..0000000 --- a/work.tex +++ /dev/null @@ -1,48 +0,0 @@ -\largesubsection{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 |