remote
Computer Vision / Machine Learning Engineer - Norbert Health
ML Engineer
Develop and deploy computer‑vision and machine‑learning algorithms for autonomous healthcare robots, enabling contact‑less vital sign capture, patient assessment, and EMR integration in real‑world clinical settings.
About the role
Key Responsibilities
- Design, implement, and optimize computer‑vision pipelines for contact‑less vital sign extraction and patient monitoring on mobile robots.
- Develop and train deep‑learning models (e.g., CNNs, RNNs) using TensorFlow or PyTorch to detect clinical events and assess patient conditions.
- Integrate AI outputs with electronic medical record (EMR) systems and robot control software to enable autonomous decision‑making.
- Collaborate with cross‑functional teams (robotics, hardware, clinical) to validate algorithms in deployed healthcare facilities.
- Maintain and improve data pipelines, annotation tools, and model deployment workflows to ensure reliability and regulatory compliance.
Requirements
- Strong proficiency in Python and experience with computer‑vision libraries (OpenCV, MediaPipe) and deep‑learning frameworks (TensorFlow, PyTorch).
- Hands‑on experience building, training, and deploying CNN/RNN models for medical imaging or vital‑sign detection.
- Understanding of real‑time inference constraints and ability to optimize models for edge deployment on robotic platforms.
- Background in healthcare AI, FDA‑cleared device development, or related clinical research is a plus.
- Excellent problem‑solving skills and ability to work in a fast‑paced, interdisciplinary environment.
Skills
pythoncomputer visionmachine learningdeep learningtensorflowpytorch