Senior Signal Processing Engineer

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. Resmed's commitment to improving the lives of people with sleep apnea and other sleep conditions through our extensive physiological and sleep data offers unparalleled opportunities for innovation.

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 about the role

As a Senior Signal Processing Engineer, you will design and develop advanced signal processing algorithms for physiological time-series data across key business areas at Resmed. Your work will directly impact the patient journey—from early disease detection to therapy optimization—by enabling accurate and robust extraction of features and biomarkers from complex, noisy signals in sleep-disordered breathing and other chronic conditions.

You will build and optimize signal processing pipelines for tasks such as filtering, denoising, segmentation, event detection (e.g., apneas/hypopneas), and feature extraction, ensuring reliability in real-world environments. 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.

Acting as both an individual contributor and subject matter expert, you will translate clinical and physiological requirements into scalable signal processing solutions, while working with cross-functional teams to improve patient outcomes and device performance.

Let’s talk 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, design experiments, and evaluate algorithm performance with a focus on accuracy, robustness, and real-time feasibility

Collaborate with Product, Clinical, and Engineering teams to translate requirements into deployable solutions on devices or cloud platforms

Ensure high-quality documentation of algorithm design, validation, and performance metrics

Mentor junior engineers and act as a subject matter expert in signal processing and time-series analysis

Contribute to intellectual property, technical publications, and regulatory documentation

Let’s talk qualifications and 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 Qualifications

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

Experience with large-scale time-series datasets (millions of signals / long-duration recordings)

Understanding of regulatory requirements in healthcare (FDA, CE, etc.)

Familiarity with real-time or embedded signal processing systems

Let’s talk about what you can expect

A supportive environment that focuses on people’s development and best implementation

Opportunity to design, influence, and innovate in cutting-edge healthcare technology

Work with inclusive global teams and open sharing of ideas

The opportunity to build impactful solutions that improve patients’ lives

A culture that encourages experimentation, iteration, and innovation