From 486043d5744f387bb6c51a6a7169b44d25923c81 Mon Sep 17 00:00:00 2001 From: Gustaf Rydholm Date: Thu, 18 Aug 2022 23:38:09 +0200 Subject: Update cv --- content/cv.md | 30 +++++++++++++++++++++++------- 1 file changed, 23 insertions(+), 7 deletions(-) diff --git a/content/cv.md b/content/cv.md index 5499fb6..a50a0eb 100644 --- a/content/cv.md +++ b/content/cv.md @@ -127,11 +127,16 @@ tbc... - Nexure AB. - Software Engineer. Aug 2021 -- Present - - bla bla + - Develop and maintain microservices for payments and subscriptions. + - Take part in architectural design discussions. + - Participated in the code review process. + - Contribute to the infrastructure with updates to k8s resources and AWS + resource management via Terraform. + - Monitor logs for bugs in different environments, e.g. staging and + production. - I develop and maintain backend web services (microservices) in the - payments/subscription domain. From time to time I also do some - infrastructure work in k8s and AWS with terraform. + *Keywords: Microservices, Kubernetes, Infrastructure, Helm, CI/CD, Kotlin, + Spring, AWS, Terraform* - Saab AB. - Machine Learning Engineer. Aug 2018 -- Aug 2021 @@ -155,8 +160,8 @@ tbc... - Developed a graph algorithm for sensor fusion. Deployed it as a microservice listing to incoming sensor data. This enabled more complex pattern analysis in downstream services. - - Improved the docker image size of microservices from ~2 GB to ~73 MB - by utilizing multistage builds and alpine base images. + - Improved the docker image size of the Python microservices from ~2 GB + to ~73 MB by utilizing multistage builds and alpine base images. - Built pipelines for CI/CD and packages deployment in Tekton. - With my docker images and pipelines we where able to reduce the average build times from ~10-30 minutes down to seconds, mostly thanks @@ -166,7 +171,18 @@ tbc... Helm, CI/CD* - Radar Warning Receiver. Aug 2018 -- Aug 2020 - - bla bla + - Built simulation software for generating realistic signal + environments with both radar and/or communication signals. Implemented + the most common signal encoding for communications, as well as + basic to SOTA radar modulations. This enabled the team to develop and + evaluate different machine learning models and ideas. + - Researched machine learning models in different stages of the radar + warning receiver, and where it would be possible computationally and + data availability. + - Held in several presentations of machine learning papers in a company + reading group. + + *Keywords: Deep Learning, Signal Processing* ### Institutions -- cgit v1.2.3-70-g09d2