About Me
I am a driven developer that takes great pride in the work I do. I believe that great software is a balance between reliability and velocity.
I thrive working in a structured way, but my daughters have taught me how to stay collected and be a voice of reason in high-stress situations.
Areas of Specialization: Backend Development, Software Architecture, Critical Infrastructure, Machine Learning, Secure Systems
Education: M.Sc. in Software Engineering (2024-2026), Syddansk Universitet
Email: patrickbjerre@gmail.com
Phone: 71200601
Location: Odense
Experience
2022 - NOW: Software Developer, Danske Inkasso
Architected and built a platform consisting of three core systems:
- A data warehouse using PostgreSQL and DuckDB, that allowed for CSV ingest with automatic schema generation, stored in Parquet.
- A business intelligence platform with KPIs and reports that could be embedded on other internal systems and keeping all data processing local.
- An ML pipeline with multiple models and a custom lead scoring model, with both drag-and-drop functionality and an MCP for natural language ML training, allowing domain experts to easily create models and test them.
C#BlazorPythonRustSQLRabbitMQDockerLinux
2024 - 2025: Software Developer, Research Project Leakage Power
Creating an ML model to classify household appliances based on energy consumption measured by IoT Devices. Reaching state-of-the-art classification with a laptop and meh CPU.
C++
Programming
Primary Languages
Languages I Know
Infrastructure & Tools
Other Technologies
Projects
| Project Name | Description | Link |
|---|---|---|
| Service-Platform | Master's Project: CyberCube Architecture: A Decentralized, High-Availability Service Platform for Critical Systems Built in Go (Collaboration with Eurisco). | - |
| Security in Robots | Bachelor's Project: Threat analysis and exploitation of Universal Robots (collaboration with the Danish Technology Institute). | - |
| Log-Parser | Built a streaming parser to convert 100GB JSON datasets to CSV to work in memory, implemented in Go. | View |
| ICU-Predictor | Deep learning model for early sepsis detection in ICU patients using Python. | View |
| Recommendation | A Q-learning song Recommendation engine, in Java. | - |
| Sand-Sim | Falling Sand simulator benchmarking Array vs. Hashmap performance, implemented using Rust. | View |