Experience
Synotis - Machine Learning Engineer
February 2024 - PRESENT
- Build end-to-end ML pipelines from problem understanding to deployed solutions for various clients
- Turn local POCs running on Jupyter Lab into production-ready ML pipelines, solving real pain points
- Interact with stakeholders to turn business problems into engineering solutions
biped.ai - Machine Learning Engineer
December 2021 - April 2023
- Responsible for the computer vision pipeline of the biped software (Python with NumPy, OpenCV, pandas, scikit-learn, open3d)
- Developed a 3D obstacle detection system running in real time on embedded hardware with 99% accuracy within 2m of the user
- Developed a ground detection system running in real time on embedded hardware with 95% accuracy within 5m of the user
- Responsible for optimising, maintaining and deploying custom-trained image detection models
- Helped bring the biped device from prototype to market
- Assembled and tested hardware
Swisscom - Master Thesis Intern
September 2020 - March 2021
- Developed a customer embedding to predict customer satisfaction under dataset shift, using different methods (random forests, deep learning, MLPs, autoencoders, semi - supervised learning, ...) and different libraries (pandas, dask, pytorch, numpy, scikit-learn).
Swisscom - Machine Learning Intern
February 2020 - August 2020
- Developed an indoor localisation method using the 4G/LTE network and CNNs (pytorch).
- Wrote a paper about it
Intel - Product Engineering Intern
March 2018 - June 2018
- Developed an Electron app (with ES6 and Vue.js) for database management, visualization and analysis.
- Developed software in Python to test the integrity of a REST API.
Skills
Note: I think these sections are silly, but everyone seems to have one. Here is a *mostly* honest overview of my skills.