Computer Vision / ML Engineer

About the role

Norbert Health is building autonomous robots that deliver healthcare. As a lead deep‑learning engineer you will drive the development of its AI‑sensing platform, creating computer‑vision models that run in real time on edge devices and enable contact‑less patient monitoring.

Key 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 combine classical signal processing with ML‑based vital‑sign extraction.
• Establish engineering best practices and reduce technical debt as the team scales.
• Contribute to the architecture and implementation of the computer‑vision stack from research to production.

Required profile

• Master's or PhD in Machine Learning or Computer Vision.
• Strong fundamentals in data structures, CV algorithms, and systems programming.
• Excellent C++ skills for edge deployment pipelines.
• 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 on resource‑constrained devices.
• Experience with PyTorch and model optimization for edge AI.

Required skills

• C++
• Python
• PyTorch
• YOLO
• InsightFace
• MediaPipe
• TensorRT
• NVIDIA Triton
• MLOps pipelines
• Quantization and pruning techniques
• Object tracking and pose estimation
• Sensor fusion (RGB, IR, depth cameras)

What we offer

• Real impact: your code provides care for patients today.
• High autonomy and technical ownership over the computer‑vision architecture.
• Work at the intersection of cutting‑edge AI, edge computing, and healthcare.
• Talented, diverse, international team tackling meaningful problems.
• Competitive salary and equity.
• Transparent, mission‑driven culture focused on continuous learning.