engineering
Posted 4 days agoSenior Signal Processing Engineer
at ResMed
Hybrid
Responsibilities
- responsibilities Design, develop, and optimize signal processing algorithms for physiological time-series data (e.g., respiratory signals, oximetry, flow signals) Build robust pipelines for filtering, denoising, artifact detection, segmentation, and feature extraction Develop algorithms for event detection and classification (e.g., apnea/hypopnea detection, respiratory pattern analysis) Work closely with Data Scientists and ML Engineers to integrate signal processing with AI/ML models Define hypotheses,
Requirements
- Let’s talk about the team Our Data Science Team is advancing Artificial Intelligence & Machine Learning (AI/ML) initiatives that drive our business in an “AI First” approach.
- On any given day, the team could be working on developing advanced signal processing pipelines for physiological data (e.g., airflow, SpO₂, respiratory effort, speech, heart-rate), extracting clinically meaningful features from billion+ nights of sleep data, improving signal quality and artifact detection, enabling robust AI/ML models, or supporting real-time patient monitoring and therapeutic interventions. Let’s talk
- You will collaborate closely with AI/ML team members to enable high-quality inputs to predictive models, and contribute to hybrid systems that combine signal processing with machine learning and deep learning approaches.
- experience PhD or Master’s in Electrical Engineering, Signal Processing, Biomedical Engineering, or a related field PhD with 2+ or Master’s with 4+ years of industry
- experience in signal processing or physiological data analysis Strong foundation in digital signal processing (DSP), including filtering, spectral analysis, time-frequency methods, and system design
- Experience with time-series analysis, including segmentation, feature extraction, and pattern recognition Solid understanding of probability, statistics, and optimization techniques
- Experience working with physiological or biomedical signals (e.g., ECG, EEG, respiratory signals, SpO₂) Proficiency in Python (NumPy, SciPy, signal processing libraries) or MATLAB
- Experience developing scalable data pipelines and evaluation frameworks Preferred
- Experience in sleep science or respiratory health Familiarity with apnea detection, sleep staging, or cardiorespiratory signal analysis
- Experience combining signal processing with machine learning/deep learning Knowledge of cloud platforms (AWS or similar) for large-scale signal data processing