About The Role

We are a medical technology company developing a vitals monitoring system. We are seeking a detail-oriented Clinical Research Coordinator to lead our data collection efforts on the ground. You will be responsible for the bridge between our hardware and "ground truth"—collecting high-accuracy blood measurements from patients to validate our proprietary sensors. Blood panels would include both fasting and non fasting measurements of HbA1c, CMP, and Lipid in addition to whatever panels the physician has ordered for the patient.

The successful candidate and partner would work alongside existing hospital clinical settings and do hardware measurements and vitals check immediately before the blood draw. The candidate will then collect test results and input them along with raw hardware data.

Key Responsibilities

• Perform or oversee venous or capillary blood draws from patient participants in a hospital setting.
• Operate and maintain non-invasive sensors, ensuring they are correctly calibrated and placed according to protocol.
• Simultaneously record sensor readings and follow up lab results with zero margin for error.
• Recruit and consent patient participants according to ethical guidelines (IRB) and local regulations.
• Ensure all collected data is anonymized, securely stored, and uploaded to our centralized database daily.
• Maintain the highest level of confidentiality regarding company technology and intellectual property.

Qualifications & Skills

• Registered Nurse (RN), Medical Laboratory Technologist, or Associates Degree in a related field with experience in clinical trials.
• Exceptional skill in blood collection to ensure patient comfort and sample integrity.
• Ability to troubleshoot early-stage hardware and navigate data-entry software.

About The Role

We are looking for a Machine Learning Engineer with a deep background in Digital Signal Processing (DSP) and Time-Series Deep Learning. You will be working alongside other bioengineers architecting the "intelligence layer" of our device. Your mission is to translate blood analyte data measured with our non-invasive sensor into isolated measurements.

Your data set will contain complex waveforms that are riddled with motion artifacts and physiological noise. We want a self starter who can take complete ownership of their area and will be expected to work autonomously with no micromanagement or hand holding. This role may include international travel as well.

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.

Qualifications

This position is not eligible for visa sponsorship (e.g., H-1B, TN, etc.). Please note that the minimum qualifications for this role are firm; only candidates who meet the listed requirements will be moved forward.

• 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.
• 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.