Dec 2023 – Sep 2024 · 9 mos

• Within Azure DevOps, I led initiatives that significantly improved the platform's test management capabilities and overall user experience. I drove the development and successful deployment of a bulk test case import/export feature for Test Plans, empowering users to efficiently manage large and complex test suites. Recognizing the critical importance of security and compatibility, I assisted the migration of the Test and Feedback extension to Manifest V3, ensuring its continued availability and mitigating potential risks. My proactive approach to problem-solving involved the identification and resolution of high-impact bugs and the swift resolution of complex production incidents, minimizing downtime and ensuring business continuity. I further enhanced the platform by refining product telemetry, enabling data-driven decision-making and contributing to a quantifiable improvement in product NPS.

Apr 2022 – Nov 2023 · 1 yr 7 mos

• As a key member of the Microsoft AppCenter team (GitHub's CI/CD for mobile apps), I led the integration of App Store Connect, streamlining the mobile app deployment process for iOS developers. I improved API performance through targeted optimizations, enhanced platform accessibility features, and remediated critical security vulnerabilities, contributing to a measurable decrease in application bugs. Furthermore, I optimized Docker images for around 10 microservices, reducing image sizes and improving deployment times. I was also responsible for managing PII-related production incidents, ensuring the security and privacy of user data.

Sep 2021 – Apr 2022 · 7 mos

• As Co-founder at AthenaSquare, I worked on the development of a assessment platform tailored for the tech industry's recruitment process. I worked on the creation of an advanced resume parser using vision and NLP models. Additionally, I engineered algorithms for parsing and ranking resumes, using data from coding platforms like GitHub and Leetcode, to make ranking to show more development skills. Our platform has been used by Upswing, SOTI, as well as Voosh.

Jan 2020 – Sep 2021 · 1 yr 8 mos · Munich Area, Germany

• At ThoughtWorks, I was involved in the development of a web application MVP, leveraging ReactJS for the frontend and Kotlin for the backend, with a strong emphasis on Clean Code, Pair Programming, and Test-Driven Development. Beyond the initial MVP, I contributed to ETL processes and optimized Neo4j database queries for managing automotive part codes. A significant aspect of my role involved scaling the Kotlin MVP to a production-ready, distributed system using Akka. This included designing an actor-based architecture to handle complex computations based on boolean algebra, determining the validity and potential solutions for various code combinations.

Jan 2019 – Sep 2019 · 8 mos · Munich Area, Germany

• During my time at Mercateo, I focused on advancing deep learning models by experimenting with encoder-decoder architectures and attention mechanisms to improve their ability to handle complex data relationships. A significant part of my work involved using the "mm_imdb" dataset to better understand and refine these models. I regularly analyzed and shared findings from new research papers with my team, helping integrate innovative practices and promoting continuous learning. My work also deepened my understanding of multimodal models, enhancing my practical skills across diverse applications.

Oct 2018 – Apr 2019 · 6 mos · Munich, Bavaria, Germany

Jan 2017 – Jan 2018 · 1 yr · Munich Area, Germany

• At OSRAM, I played a key role in developing and enhancing real-time object detection and tracking systems. My contributions included:
• Real-Time Object Detection and Tracking: Implemented the Yolo and Siamese deep learning algorithms for object detection and tracking tasks, focusing on improving the system's accuracy and operational efficiency.
• Dataset Design and Development: Led the design of workflow processes and creation of a synthetic dataset tailored for person tracking tasks, which supported more effective model training and validation.
• Algorithm Evaluation: Conducted thorough evaluations of various detection and tracking algorithms using our custom-created dataset, assessing their performance to identify the most effective solutions for practical deployment.
• This role allowed me to apply my skills in deep learning and algorithm implementation effectively, contributing to enhancements in automated object detection and tracking technologies.