Job Summary:
Norbert Health is building autonomous robots that deliver healthcare. They are seeking a lead deep learning engineer to spearhead the development of their groundbreaking sensing technology, focusing on designing and deploying computer vision models for real-time inference.
Responsibilities:
• Design, fine-tune, and deploy computer vision models (YOLO, InsightFace, MediaPipe, facial landmark detection, object tracking, pose estimation) for real-time inference on the edge
• Optimize models for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton
• Build and maintain MLOps pipelines for model training, validation, and performance monitoring
• Develop video processing pipelines that integrate with both classical signal processing and ML based vital sign extraction
• Establish engineering best practices and help reduce technical debt as we scale
• Contribute to the architecture and implementation of the computer vision stack from research to production
Qualifications:
Required:
• Master's or PhD degree in Machine learning / Computer vision
• Strong fundamentals: data structures, CV algorithms, and systems programming
• Strong C++ skills - this is critical for our edge deployment pipeline
• Solid Python proficiency for ML experimentation and tooling
• Ability to work independently, solve complex problems, and drive projects to completion
• 5+ years experience deploying computer vision models to production, ideally on resource-constrained devices
• Experience with PyTorch and model optimization for edge AI
• Proven ability to take models from research to production on embedded hardware
Preferred:
• Experience with NVIDIA Jetson platform, TensorRT, or Triton Inference Server
• MLOps experience (experiment tracking, model versioning, performance monitoring)
• Experience with sensor fusion (RGB, IR, depth cameras)
• Background in medical devices, regulated environments, or healthcare applications
• Experience working in fast-moving early-stage environments
Company:
Norbert Health develops a home medical pod that monitors the health of families using contactless sensors. Founded in 2019, the company is headquartered in Brooklyn, USA, with a team of 11-50 employees. The company is currently Early Stage.