Here you can find my detailed resume

Sense6 is a forward-thinking AI company that specializes in leveraging machine learning to extract and interpret complex data. Our innovative approach transforms raw data into actionable insights, enabling businesses to make data-driven decisions with precision and ease. At Sense6, we're dedicated to pushing the boundaries of what's possible with AI and machine learning technologies, providing tailored solutions that drive efficiency and growth.

In my role as a Machine Learning Engineer, my responsibilities include:

• - I enhance data extraction from structured PDFs by integrating machine learning techniques with heuristic algorithms, significantly improving result accuracy.
• - Maintenance of the codebase including managing a poetry environment and Dockerfile, along with our MongoDB.
• - I design and implement test cases, monitored through Jira, to maintain the integrity and efficiency of our solutions.
• - I also provide strategic guidance on data analysis, helping clients harness the power of data for impactful business results.
• - I also get to interview software developer candidates, helping to find the right people who fit well with our team's innovative spirit and tech requirements.

I'm a teacher at Le Wagon, where I help students dive into the world of data and start new careers. I love supporting students in reaching their goals and seeing them succeed. The main tasks:

• - Teaching classes on the latest in data science and analytics.
• - Guide projects: Help students with hands-on projects that teach them real skills.
• - Personalized feedback: Look at student assignments and give feedback to help them improve.
• - Career advice: Give students tips and encouragement as they step into their new data careers.

Some of my favourite topics as data visualization, machine learning models, performance metrics, SQL and DBT.

As a Data Science Intern at Parquery, I was part of a small development team in a startup setting. I saw firsthand how an agile team can efficiently handle a large workload. We operated on a fast-paced agile schedule, with three-week sprints followed by a week of varied tasks. Here are my main contributions:

• - Participated in the agile process, from planning to stand-ups, client demos, and team retrospectives.
• - Developed solutions to handle big data of data over Google Cloud to process and prepare datasets for further model training.
• - Built and fine-tuned object recognition, object tracking and image classification pipelines, achieving over 97% accuracy.
• - Worked on both back-end (Python, C++, SQL) and front-end (JS, Vus.js) development, fixing bugs and adding new features.
• - Maintaining our environment using tools like Poetry, Docker, and a PostgreSQL database.

In my role as a Research Assistant at the Ontology Engineering Group (OEG) I carried out research focused on classifying research software for enhanced discoverability and reproducibility. This work was substantial enough to form the basis of my master's thesis, which introduced a new way to automatically sort software by what it does and the scientific area it's used in. Here are the key outcomes:

• - Developed a novel classification system that intelligently grouped software repositories without the need for retraining classifiers when new categories were added.
• - Devised strategies for incorporating new, labelled datasets and preparing documentation for successful software project classification.
• - Attained a 92% F1 score during training and a 76% F1 score on the test set, significantly surpassing the state-of-the-art’s 36% score.
• - Successfully incorporated the classification methodology into an existing software metadata extraction framework.

As a Machine Learning Intern at Ericsson, I contributed to the enhancement of CodeChecker, focusing on a feature to rate bugs by importance and ease of resolution. This project aimed to streamline the developers' workflow by prioritizing bug fixes:

• - Engaged with senior C++ developers to identify key pain points, leading to a feature design that addressed the top 5 most common bug detection issues.
• - Conducted a comparative analysis of state-of-the-art code representation techniques, (ex. word2vec) and developed an approach for C++.
• - Curated a dataset with 2,000+ instances of bug samples, each manually labelled to distinguish between false positives and negatives, increasing the model's precision by 20%.
• - Developed and tested 5+ ML models, that prioritized the found bugs.
• - Presented findings to senior management that demonstrated a potential 40% reduction in developers' time spent on bug resolution, influencing the adoption of the new tool.
• - Created comprehensive documentation and transitioned the project effectively.

At Ericsson, I was working on the development of telecommunication software with a functional programming language called Erlang. My experience with Erlang started during my bachelor's thesis project when I worked on RefactorErl a static analyser tool, which performs static analysis on Erlang code. I helped set up this tool at Ericsson, which was my first big task here. This project not only introduced me to functional programming but also became the springboard for my first initiative at Ericsson—integrating RefactorErl into the company's internal systems. Here are the tasks I've been involved in:

• - Developing and maintaining robust telecommunication software with Erlang, serving millions of users globally, ensuring high performance and reliability.
• - Implemented test cases covering both unit tests to check individual code pieces and functional tests to ensure the entire system ran smoothly.
• - Handling version control with Git across multiple codebases, ensuring efficient code integration and deployment for consistent and smooth software updates.
• - Using Jira for task management within an Agile framework, to ensure that my work is well-organized and aligned with our team's development.

I worked as a Teacher Assistant at Eötvös Loránd University for 7 semesters, where I taught various practical classes for computer science bachelor’s students. My responsibilities included preparing material and teaching practical class sessions, putting together exams and projects that fit what was taught and offering full support to help students succeed. Here's more about the specific classes:

• - Algorithms and data structures I, II (2 semesters): Guided students through various algorithms and data structures that complemented their lectures. We delved into graph algorithms like Dijkstra's shortest path, Floyd's algorithm, and breadth-first/depth-first search, as well as fundamental structures like linked lists and hash tables. I also introduced sorting algorithms such as quicksort and mergesort, and tree structures like binary search trees and heaps.
• - Web development (3 semesters): Educated students on creating responsive websites, starting from concept wireframes to building functional sites with HTML5 and CSS3. We covered front-end frameworks, user experience fundamentals, and client-side scripting with JavaScript. Students completed two key projects: designing a wireframe and developing a live website, which I evaluated based on a detailed list of technical and design requirements.
• - Theory of computation (2 semesters): Worked with students on exercises related to the foundations of computation theory. This included formal language theory, converting grammars to Chomsky normal form, designing finite state machines, and understanding the principles of Turing machines. We also explored complexity theory and algorithmic decidability to provide a comprehensive understanding of computational limits.

• Joint master's degree in data science. First year at ELTE in Budapest, second year at UPM in Madrid.
• Minor in Innovation and Entrepreneurship.
• Thesis: A methodology for research software classification, can he found: here.

During my time at Angloville, I had the opportunity to engage in English language teaching for junior learners in Poland. My role primarily involved leading personalized educational sessions with small groups of one to two students, focusing on topics selected by the learners. In addition to these teaching responsibilities, I played a collaborative role in assisting the organizers with various group activities.