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#Deep Tech · AI · Sensors · Diagnostics
About the Company - Nanological is a CSIC spin-off developing a breakthrough diagnostic platform for the rapid and precise detection of sepsis.
Our proprietary system integrates microfluidics, optomechanical sensing and machine learning to identify pathogens directly from blood within minutes.
We've been recognized as a Deep Tech Pioneer by Hello Tomorrow, selected among the Top 100 startups by APTE and awarded by EIT Health, Comunidad de Madrid and the Spanish Ministry of Equality for our innovation and clinical impact.
About the Role - We are looking for a Machine Learning Engineer with strong foundations in signal processing and a product-oriented mindset.
You'll work with real sensor data to extract bacterial signatures and building a robust, scalable ML subsystem for integration into a regulated diagnostic product.
Define and track sensitivity/specificity and other performance metrics
Ensure compatibility with embedded and cloud-based integration
Help lay the foundations of a production-ready ML subsystem
Degree in Electrical Engineering, Physics, Mathematics, Computer Science or a related field
~2–4 years applying ML and signal processing to real-world sensor or experimental data
~ Experience working in cross-functional teams (hardware and software)
