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Founder & CEO, Feretix | On-device ML from raw sensor data
I build ML systems that run where the data is generated: on-device, on constrained hardware, inside real products. At Feretix, we convert raw sensor streams into deployable, real-time prediction modules. The system learns directly from raw signals, without manual feature engineering. Hardware teams receive a standalone inference module that integrates directly into their stack. No retraining pipeline. No cloud dependency. Data stays on the device. Before Feretix, I spent a decade in Silicon Valley as CTO across multiple startups, shipping over two dozen ML products into production across industrial systems, robotics, and embedded hardware. That track record is the foundation this company is built on. PhD in machine learning, Max Planck Institute. MS in Physics, EPFL. Research at NYU and Caltech. Background in signal processing, embedded ML, and physics-constrained inference. If you are building hardware and evaluating how to embed reliable intelligence without building an ML team, talk to me before you commit to an architecture. https://feretix.ch
Max Planck Society
Doctor of Philosophy (Ph.D.), Machine learning
January 1, 2001 – January 1, 2004
Centrale Lyon
Master of Science (M.S.), Fluid dynamics
January 1, 1999 – January 1, 2000
EPFL
Master of Science (B.S. and M.S.), Physics and machine learning
January 1, 1995 – January 1, 2000
feretix SA
Founder & Chief Executive Officer
January 1, 2025 – Present
Pully, Switzerland
Symphony Diagnostics
Co-founder
January 1, 2023 – Present
San Francisco Bay Area
Happy Health
Director of ML and Data Sciences
February 1, 2021 – October 1, 2022
Austin (remote)
Artif Wonder
Co-founder
September 1, 2019 – Present
Greater Los Angeles Area
Kernel
Head of ML
April 1, 2019 – September 1, 2019
Los Angeles Metropolitan Area
Entefy
Director of AI/ML engineering
November 1, 2017 – April 1, 2019
San Francisco Bay Area
BootstrapLabs
Investor and advisor
December 1, 2014 – September 1, 2017
San Fransisco
Synaptics
Staff Systems Architect
June 1, 2014 – November 1, 2017
San Francisco Bay Area
California Institute of Technology
Research Scholar in Machine Learning and Brain-machine interfaces
May 1, 2008 – June 1, 2014
Los Angeles Metropolitan Area
New York University
Research Scholar in Machine Learning and Visual Neuroscience
October 1, 2004 – May 1, 2008
New York City
Ecole polytechnique fédérale de Lausanne
Research Assistant
January 1, 1995 – January 1, 2000
Cultural Fit Analysis
The candidate's career trajectory, marked by founding multiple companies and holding senior leadership roles in innovative tech firms, strongly aligns with a 'Founder' target role. Their diverse project experience across industrial, biotech, wearable sensors, and brain-machine interfaces demonstrates adaptability and a broad interest in applying ML to various domains. This entrepreneurial spirit and breadth of technical application suggest a strong cultural fit for a dynamic, high-growth, and innovation-driven environment.
Soft Skills & Operational Fit
The candidate's extensive experience in leadership, co-founding multiple companies, and advising startups suggests strong soft skills in team leadership, communication, and strategic thinking. Their history of building and deploying complex ML systems indicates operational fit for driving technical initiatives from conception to deployment, especially in constrained environments. The descriptions highlight product-oriented thinking and the ability to translate research into practical applications.