Experience

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  Mhp – a porsche company

  Jul 2018 - Aug 2018

  Summer intern

  Worked on a web application in a team of 6 students.

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  Bosch

  Jul 2019 - Apr 2020

  Software development intern

  Worked on image segmentation for driving assistance systems using deep learning methods.

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  Imogen research institute

  Apr 2020 - Aug 2020

  Research assistant

  • Worked on whole-heart semantic segmentation from MRI images with deep learning. • Developed a comprehensive, end-to-end pipeline that included data processing, identification of suitable architectures, as well as training and evaluation of the models.

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  Ergon informatik ag

  Jan 2021 - Sept 2021

  Machine learning intern

  • Contributed to the development of a machine learning-powered system designed to detect fraudulent activities in banking transactions.• Enhanced the optimization process of the machine learning models by replacing random point sampling with more efficient Bayesian hyperparameter tuning techniques.• Implemented analysis methods to gain quantitative insights into the contribution/importance of various predictive features to improve the interpretability of the models and reduce overfitting on noise.• Refactored an existing codebase using OOP concepts and created a testing suite to improve reliability, readability, and maintainability. Weniger anzeigen

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  University of zurich

  Jul 2022 - Jan 2022

  Research assistant

  • Helped develop an emotion downregulation training system. The core working principle of the system is providing real-time feedback on downregulation success based on real-time fMRI and pupil dilation data.• Implemented an experiment based on the presentation of visual stimuli while simultaneously measuring the pupil using the Eyelink Toolbox, followed by real-time data analysis and feedback presentation.• Analyzed data obtained from volunteers who participated in the experiment, subsequently providing individualized as well as population-level statistics. Additionally, I presented the data visually via comprehensive tables and plots.• Ensured the system is reliable and easy to use for scientists by adding numerous early-failure checks and tests, which effectively mitigate the risk of manual errors during experimental runs. Weniger anzeigen

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  Blp digital ag

  Aug 2023 - now

  Devops engineer

  - Overhauled Microservice Orchestration: Improved the reliability, observability, and error handling of our internal microservice orchestration system. This involved a detailed analysis of industry-standard tools to identify those that best met our current and future requirements in terms of cost, scale, and features. The system ensures that infrastructure errors (network issues, disk/memory pressure, etc.) are separated from domain/application logic, allowing developers to focus exclusively on the core business. Core technologies: Kubernetes, Temporal.- Led Infrastructure as Code (IaC) Adoption: Led the company-wide adoption of IaC, designing and implementing a scalable system that accommodates multiple teams and environments. The system prioritized ease and safety of use, significantly accelerating infrastructure development, enhancing explainability, and improving security. Core technologies: Terraform, GCP.- Enhanced K8s Deployment System: Drawing inspiration from AWS CDK(8s), I revamped the existing Kubernetes deployment/configuration strategy. I replaced manually written YAML—which was prone to errors and difficult to iterate on as the number of services grew—with a type-safe, testable, and reliable framework for automatically generating YAML. This greatly reduced common configuration mistakes, enhanced maintainability, and significantly improved development speed. Furthermore, the framework promotes seamless code reuse, enabling crucial configuration (e.g., security settings) to be consistently applied across the entire deployment. Core technology: TypeScript. Weniger anzeigen