- Inicio Inmediato: Machine Learning Engineer – Signal Processing

buscojobs España; Madrid; Presencial; EUR 35.000 - 55.000; Jornada completa

Descripción de la vacante

A leading company is seeking a Machine Learning Engineer specialized in signal processing to work on groundbreaking diagnostic technology. This role involves analyzing sensor data, developing ML models, and contributing to a product that aims to revolutionize pathogen detection in clinical settings. The ideal candidate will have a strong foundation in ML, experience with cross-functional teams, and a product-oriented mindset.

Servicios

Competitive compensation

Opportunities for professional growth

Technical ownership from day one

Formación

• 2–4 years of experience applying ML and signal processing.
• Experience in ML pipeline development.
• Proven ability to work in cross-functional teams.

Responsabilidades

• Analyze and process sensor signals for diagnostics.
• Develop and evaluate ML models for bacterial classification.
• Build modular, reusable code for signal processing.

Conocimientos

Python

Signal Processing

Machine Learning

Data Analysis

Educación

Degree in Electrical Engineering, Physics, Mathematics, or Computer Science

Herramientas

NumPy

pandas

scikit-learn

PyTorch

TensorFlow

Docker

Descripción del empleo

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Machine Learning Engineer – Signal Processing for Diagnostics Madrid (Parque Científico) | On-site with 1 remote day / week Deep Tech

• 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.This is a unique opportunity to shape a high-impact diagnostic product based on deep technology. ResponsibilitiesAnalyze and process optomechanical sensor signals to enhance signal-to-noise ratio and to extract diagnostic-relevant featuresDevelop and evaluate ML models for bacterial classificationBuild modular, reusable code for signal processing and model pipelinesDefine and track sensitivity / specificity and other performance metricsEnsure compatibility with embedded and cloud-based integrationHelp lay the foundations of a production-ready ML subsystem QualificationsDegree in Electrical Engineering, Physics, Mathematics, Computer Science or a related field2–4 years applying ML and signal processing to real-world sensor or experimental dataProven experience in ML pipeline development and product-aligned implementationExperience working in cross-functional teams (hardware and software) Technical SkillsStrong Python (NumPy, pandas, scikit-learn, PyTorch / TensorFlow)Solid understanding of signal processing (filtering, spectral analysis, feature extraction)Experience with ML classification models and deep learning frameworksFamiliarity with CI / CD, version control, modular design and DockerBonus : experience in C++ or embedded system development Why Join NanologicalContribute to a first-of-its-kind medical product with real clinical impactJoin a highly skilled, mission-driven teamGain technical ownership from day oneCollaborate with leading research and clinical institutionsCompetitive compensation and real opportunities for professional growth Equal Opportunity - Nanological is an equal opportunity employer. We value diversity and are committed to creating an inclusive and respectful workplace for all. How to Apply - Send your CV and a short introduction to
• you're ready to build something meaningful — we'd love to hear from you.

Seniority level

Seniority level

Entry level

Employment type

Employment type

Full-time

Job function

Job function

Information Technology

Business Consulting and Services

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