Work experience

IPercept (June 2024 - May 2025)

  • Development of a cross-platform desktop application in Python, using Qt-based PySide6.
  • Management and creation of Grafana alerts and dashboards.
  • Profiling and optimization of Python code, especially related to the pandas and polars libraries.
  • Close work with matplotlib for data visualization.
  • Set-up of a remote development environment, used company-wide.
  • Supervision of my Master’s thesis.

Handyhand (February 2023 - June 2023)

  • Full-stack (Angular.js/React Native + Node.js) development, mainly with the Node.js backend and PostgreSQL.
  • Focus on creation & integration of AI-related tools, such as a listing price predictor or an AI customer service chatbot.
  • Supervision of my Bachelor’s thesis - “Geographical data enrichment service”, using computer vision. This service ended up being integrated into Handyhand’s product.

Kvalifik (September 2022 - January 2023)

  • Full-stack web and mobile development (React, React Native front-ends)
  • GraphQL + PostgreSQL stack, deployed in Google Cloud and using Firebase
  • Worked across smaller teams dedicated to different clients

GOCO (May 2021 - May 2022)

  • Full-stack development of web and mobile solutions
  • AWS stack + Serverless backend, closely worked with AWS services such as DynamoDB, Cognito, S3 and Lambda (Serverless functions)
  • React and React Native front-ends
  • Close communication with customers, leading smaller projects

Education

MSc Software Engineering of Distributed Systems @ KTH (2023 - 2025), Stockholm

  • Specialization in advanced distributed systems, search engines and ML (LLMs, speech, large scale datasets)
  • Master’s thesis on IoT-cloud communication, made in collaboration with IPercept

BSc Software Development @ KEA (now EK) (2022 - 2023), Copenhagen

  • Introduction to distributed systems and applied AI. Other topics included testing, development in Django, and system’s integration.
  • Bachelor’s thesis titled “Geographical data enrichment service”. Built in Google Cloud, the service relied on computer vision to abstract useful data from satellite/aerial images of Danish properties. Built using Python (ML using Meta’s SAM), a Ts.ed API, Prisma and PostgreSQL.

Computer Science AP degree @ UCN (2019 - 2022), Aalborg