What We’re Looking For

• 3–6 years of experience in machine learning, with hands-on experience in time-series analysis, signal processing, or physiological data (audio, wearables, etc.).

• Solid understanding of statistics and the ability to validate and tune models using real-world, often noisy data.

• Strong Python skills and experience with NumPy, SciPy, Pandas, scikit-learn, PyTorch or TensorFlow.

• Experience working with biometric, medical, or audio data is a big plus.

• Familiarity with GCP or cloud-based ML workflows (Vertex AI, BigQuery, etc.) is nice to have.

• Bonus: Knowledge of sleep science, DSP, or personalization systems.

• Strong communication skills — you’ll be working across domains with product and audio experts.

What You’ll 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 time-series data, including signal preprocessing, noise suppression, and real-time analysis.

• Collaborate closely with the CTO (ex-Microsoft ML lead) and a multidisciplinary team to shape the product's intelligence layer.

• Translate scientific insights into production-ready pipelines that personalize audio feedback in real time.

• Contribute to research and experimentation with adaptive audio response systems.