<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p>RespireLabs is hiring a <strong>Machine Learning Engineer / Scientist</strong> in Vienna to work on multimodal sleep and breathing signal research.</p><p>We are building privacy-first R&amp;D prototypes around under-nose sensing, Smart Mouth Tape, breathing sounds, airflow, SpO2, sleep position, nasal-cycle dynamics, polygraphy validation and personalised breathing intervention research.</p><p>You will help us turn noisy, real-world breathing and sleep recordings into research-grade features, models and validated findings.</p><p><br/></p><p><strong>What you will work on</strong></p><p><br/></p><p>You will work on preprocessing, feature extraction, signal quality checks, supervised and unsupervised learning, classification models, biomarker discovery and model validation. The role covers polygraphy datasets, prototype recordings, breathing events, airflow limitation, oxygen drops, left/right airflow asymmetry, sleep-position signals and intervention-response patterns.</p><p>You will also document model assumptions, model limits, evaluation metrics, bias risks, dataset quality problems and negative results. This is important because our work is research-stage and non-diagnostic.</p><p>You will build data pipelines for ingestion, cleaning, annotation support, dataset versioning, feature storage, experiment tracking, model-training handoff, model-output tracking and research reporting.</p><p>You will help ensure that every dataset snapshot, preprocessing step, model version, evaluation result and export can be traced later. This matters because the project must be scientifically reproducible, GDPR-aware and ready for grant reporting and audits.</p><p><br/></p><p><strong>You may be a strong fit if you have</strong></p><p>Experience with Python, machine learning, biomedical signals, audio/sensor data, time-series modelling, statistics, signal processing, model validation or applied health-data research. </p><p><br/></p><p>Good to have: Experience with data engineering, MLOps, cloud storage, databases, APIs, CI/CD, data versioning, experiment tracking, secure data handling and ML workflow automation.</p><p><br/></p><p>Experience with health data, wearable data, audio/time-series data, GDPR-sensitive systems, clinical research datasets or biomedical ML pipelines is a strong advantage.</p><p><br/></p><p><strong>What we care about</strong></p><p><br/></p><p>The goal is not only to “make the pipeline run.” The goal is to make the research reliable: versioned datasets, clear lineage, reproducible training runs, safe access controls, useful logs, privacy-by-design and documentation that can survive external review.</p><p><br/></p><p>Send your CV, LinkedIn profile and a short note about why this project fits you.</p><p><br/></p><p><strong>Important note:</strong> RespireLabs is working on research-stage, non-diagnostic technology. We do not claim to diagnose, treat or replace clinical sleep testing.</p> </div>