Senior Signal Processing Engineer Health Wearable SNR

Liom; Zürich; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Benefits dieser Stelle

Work/Life Balance

Diversity

Mentorship & Career Growth

Amazing team

Zusammenfassung

Liom in Switzerland is seeking a Senior Signal Processing Engineer to collaborate with experimental and ML experts to develop methods that improve SNR and identifiability of our non-invasive multi-biomarker smartwatch measurements.

You will apply signal processing, system identification, control theory, and machine learning across disciplines, with a strong emphasis on research, code in Python and C/C++, and delivering real-world solutions.

Qualifikationen

• Advanced degree in a related field with strong signal processing background.
• 3+ years applying signal processing, control theory, and system identification, preferably in low-SNR settings.
• Strong mathematical background in signal processing, system identification, statistics, or ML theory.
• Ability to digest scientific literature across cross-disciplinary domains.
• High attention to detail and ability to manage multiple priorities in a dynamic environment.
• 3+ years writing software in Python and at least one compiled language (C/C++, Rust).
• 3+ years of experience in industry or applied environments.

Aufgaben

• Develop new methods to optimize SNR and identifiability of measurements.
• Combine signal processing, system identification, and machine learning techniques to build solutions.
• Collaborate with experimental, ML, and domain experts to address real-world problems.
• Publish findings and contribute to the implementation of deployable solutions.

Kenntnisse

Signal processing

System identification

Control theory

Literature review

Multidisciplinary collaboration

Ausbildung

Master's / PhD in Engineering, Science, or Mathematics

Tools

Python

C/C++

Rust

Jobbeschreibung

Liom in Switzerland is seeking a Senior Signal Processing Engineer to collaborate with experimental and ML experts to develop methods that improve SNR and identifiability of our non-invasive multi-biomarker smartwatch measurements.

You will apply signal processing, system identification, control theory, and machine learning across disciplines, with a strong emphasis on research, code in Python and C/C++, and delivering real-world solutions.