We are looking for a Data Scientist / ML Engineer with a biomedical signal processing background to support development of real-time AI solutions based on physiological signals. The role begins with consulting, followed by hands-on model training and optimization during Phase 3 of product development. The ideal candidate has experience working with messy physiological datasets, including ECG, EEG, EOG, brain waves, or other low-frequency biosignals, and is comfortable building end-to-end ML pipelines

from signal filtering and feature engineering to real-time model deployment.

Biomedical engineering background Neuroimaging or electrophysiology experience Experience working with multi-source physiological datasets Experience building reproducible research pipelines Experience with real-time ML solutions PyTorch / TensorFlow experience Engagement Model Phase 1–2: Consulting / Advisory Phase 3: Model Training & Implementation Real-time biosignal AI product Apply NowMore OpeningsNew Jersey, NJBrazil, RemoteMiami, RemoteUSA, RemoteRemotely, RemotelyShare This JobPowered by

Phase 1–2: Consulting & Architecture Analyze physiological signal datasets and data quality Recommend signal preprocessing and filtering strategies Define feature engineering approach for biosignals Suggest model architecture for real-time predictions Advise on data pipeline and training strategy Help define evaluation metrics and validation approach Phase 3: Model Training & Implementation Process low-frequency physiological signals (ECG, EEG, brain waves, biosignals) Apply signal filtering, noise reduction, and transformations Build feature extraction pipelines from physiological data Train and optimize machine learning models Support real-time inference and model performance optimization Work closely with engineering team for model integration Improve model accuracy through experimentation and iteration Required Experience 2+ years experience as Data Scientist / ML Engineer / Biomedical Data Scientist Strong signal processing background Experience working with physiological or biomedical signals such as: ECG EEG EOG Brain waves Other biosignals Experience working with low-frequency signals Experience handling noisy or heterogeneous physiological datasets Hands-on experience with: Signal filtering Mathematical filters Feature extraction Time-series analysis Python skills: NumPy SciPy Pandas Scikit-learn