My Expertise

Hi! I’m Mikołaj, a software engineer intern and a student at Warsaw University of Technology, with a passion for music. My professional journey includes an internship at Allegro and a current position as a software engineer intern at Bridgestone. My technical expertise encompasses Java, DevOps, Kubernetes, Kafka, Spring, and React. Alongside my engineering roles, I’ve competed in coding competitions, securing 3rd place in the Best Hacking League and 2nd place in the Ensemble AI Hackathon. Academically, I'm focusing on machine learning, particularly within my thesis on “Conditioning of Musical Generative Models.”
Thanks for stopping by!

Software engineering

Proficient in Java and Spring Framework for robust application development. Skilled in Python, C/C++, and database management (SQL, NoSQL). Knowledgeable in design patterns, TDD, DDD, and microservices for scalable solutions.

DevOps and BigData

Skilled in DevOps with Kubernetes for application deployment and architecture, ensuring scalability. Experienced in Kafka for data streams and Azure for cloud-based solutions, focusing on performance and reliability.

ML and Data science

Familiar with machine learning, applying PyTorch in university research. Comfortable using R and Pandas for data analysis. Solid mathematical background, aiming to utilize statistical models and algorithms for data-driven insights.

Featured Projects

Parcel Tracking System

Java, Spring Boot, Resilience4j, React
Apache Kafka, MinIO, Hashicorp Vault
Docker, Jenkins

Microservices-based Parcel Tracking System. It allows clients to add and track shipments using unique tracking numbers. The system integrates with various carriers for precise shipment location tracking. Key features include local database storage of tracking history and automatic updates for registered shipments. The system also supports searching across all shipment attributes and offers functionality for printing tracking histories, with files stored in a dedicated resource.

Check it out

Song skip prediction

Sklearn, Tensorflow
Pandas, numpy, seaborn

This project is a part of the Machine Learning Engineering at Warsaw University of Technology course aimed at developing a practical solution for "Pozytywka," an online music streaming service. As analysts, we step into the role of tackling a vaguely described task, requiring us to specify details for implementation. The challenge involves understanding the problem, analyzing data, and sometimes negotiating with management (tutor) to ensure the models are production-ready and future-proof for subsequent versions.