36 years of experience in machine learning with handson experience in timeseries analysis signal processing or physiological data (audio wearables etc..
Solid understanding of statistics and the ability to validate and tune models using realworld often noisy data.
Strong Python skills and experience with NumPy SciPy Pandas scikitlearn PyTorch or TensorFlow.
Experience working with biometric medical or audio data is a big plus.
Familiarity with GCP or cloudbased ML workflows (Vertex AI BigQuery etc. is nice to have.
Bonus: Knowledge of sleep science DSP or personalization systems.
Strong communication skills youll be working across domains with product and audio experts.
What Youll Do
Design and implement machine learning models to detect and predict sleep states (REM NREM awake) and biometric signals (like breathing rate) from audio or sensor data.
Work with timeseries data including signal preprocessing noise suppression and realtime analysis.
Collaborate closely with the CTO (exMicrosoft ML lead) and a multidisciplinary team to shape the products intelligence layer.
Translate scientific insights into productionready pipelines that personalize audio feedback in real time.
Contribute to research and experimentation with adaptive audio response systems.
Help shape a strong engineering culture that balances technical excellence with user empathy.
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