Hidden Folks · 1 day ago
Machine Learning PPG & Radar Signal Processing Engineer
Chicago, IL
Full-time
Onsite
Mid, Senior Level
3+ years expHidden Folks is seeking a Machine Learning Engineer with expertise in Digital Signal Processing and Time-Series Deep Learning. The role involves designing and implementing pipelines for processing complex blood analyte data and developing machine learning models to enhance the functionality of their non-invasive sensor technology.
Computer Games
No H1B
U.S. Citizen Only
Responsibilities
Design and implement robust pipelines to clean and normalize raw "sawtooth" waveforms from sensors
Build and train Deep Learning models (CNN-LSTMs, Transformers, or State-Space Models) to perform regression on physiological signals to estimate blood-constituent volumes
Extract morphological and frequency-domain features (Pulse Arrival Time, Pulse Area, Harmonic Ratios) that correlate with blood viscosity and analyte concentration
Develop "Biosignal Intelligence" layers to detect and reject "bad data" caused by motion, skin-tone variations, environmental interference, etc
Conduct rigorous error-grid analysis (e.g., Clarke Error Grid) and validation against "gold standard" invasive lab results
Qualification
Required
MS or PhD in Biomedical Engineering, Computer Science, or Electrical Engineering with a focus on ML/Signal Processing, or equivalent experience
Solid software development experience in C, C++, and Python
3 or 5 years of proven experience building regression ML models for time-series data using PyTorch or TensorFlow
Deep understanding of the physics of IR, Photoplethysmography (PPG) and/or RF sensing
Mastery of Digital Signal Processing (FFTs, Wavelet Transforms, Adaptive Filtering)
Applicants must be currently authorized to work in the United States on a full-time basis
Company
Hidden Folks
A game studio.
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase