Angelica Hjelm Gardner

Ericsson

Scrum Master & Cloud Native Developer • Aug, 2022 — Now

• Develop and maintain two Golang microservices within the Observability area, which are deployed in a Kubernetes environment as part of cloud-based infrastructure supporting 5G services.
• Faciliate Scrum ceremonies, including stand-ups, sprint planning, retrospectives, and sprint reviews.
• Assist the product owner with product backlog management and prioritization.
• Participated in technical interviews to recruit junior developers and onboarded new team members.

Simple [A]

Software Developer Intern, R&D • Jan, 2019 — Jun, 2019

• Remote, project-based internship to develop a content-based recommendation system.
• The module supported their chatbot system during fallback intent to improve the user experience.

Mjukhud.se

Junior Web Developer • Jan, 2015 — Dec, 2016

• Improved the responsiveness of the Magento e-commerce site and WordPress blog using HTML, CSS (Bootstrap), and JavaScript, leading to a better user experience across devices.
• Assisted with minor Back End fixes and implemented Magento security patches, ensuring site stability and security.
• Conducted performance testing and implemented Front End optimization techniques, resulting in faster load times and improved PageSpeed Insights scores.

Linnaeus University

Master of Science with specialization in Software Technology, Computer Science • 2020 — 2022

• Coursework on formal methods, machine learning, code transformation and interpretation, visualization, and data mining, complemented by hands-on projects for practical experience.
• My degree project was to conduct ML experiments in Jupyter notebooks to recognise pain, estimate intensity, and classify painful body areas in adults based on body movements and facial expressions. I used a hybrid CNN-BidirectionalLSTM and a recurrent CNN (RCNN) with Keras Functional API (Tensorflow 2).

Linnaeus University

Bachelor of Science, Computer Science • 2019 — 2020

• Coursework on algorithms, software architecture, design patterns, and software testing.
• My degree project was to design and execute controlled experiments using Sacred to evaluate the performance of deepfake detection. The study compared the effectiveness of ensemble models versus single models, utilizing the Deepfake Detection Challenge dataset from Kaggle. The following Convolutional Neural Network (CNN) architectures were implemented with PyTorch VGG19, ResNet50, VGG16, and Xception.

Mid Sweden University

Higher Education Diploma with specialization in Web Development, Computer Engineering • 2017 — 2019

• Focus on full-stack web development, combining theoretical foundations with hands-on practical experience.
• My degree project was to develop a content-based recommendation module with four components (1) web spider using DotnetSpider, (2) bag-of-words model using ML.NET, (3) Neo4j graph database and (4) GraphQL API to which the chatbot agent connects via Dialogflow's webhook service.

GitHub Profile

Developer & Contributor

You're welcome to explore my open-source contributions and personal projects on my GitHub profile. I regularly upload coding challenge solutions, new learnings and degree projects.

Languages

HTML, CSS (basic), Python, Golang, Bash

Tools & Technologies

Git, Docker, Kubernetes & Helm