Norbert is building autonomous robots that deliver healthcare. Our AI sensing platform mounts on mobile robots and does the work of a care team member—rounding on patients, capturing vitals without contact (FDA‑cleared for pulse and respiratory rate, more in the pipeline), running assessments, documenting to the EMR, and escalating when something's wrong. Autonomously. We're not building demos. We're deployed in real facilities today, monitoring hundreds of patients daily. We're solving one of healthcare's hardest problems: a global nursing shortage that will hit 40% by 2030. We're a small, international team backed by top‑tier VCs, with offices in Brooklyn and Paris. We ship things that matter.

The position
We are looking for our lead deep learning engineer to spearhead the development of our groundbreaking sensing technology.

What you will do:

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





What we look for:

Master's or PhD degree in Machine learning / Computer vision

Strong fundamentals: data structures, CV algorithms, and systems programming

Solid 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

Nice to haves:

Experience with NVIDIA Jetson platform, TensorRT, or Triton Inference Server

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

What we offer:

Real impact: your code provides care for patients today

High autonomy and technical ownership - you'll shape our computer vision architecture

Work at the intersection of cutting‑edge AI, edge computing, and healthcare

A talented, excellent, diverse and international team

Cutting‑edge stack: embedded AI, robotics, LLMs, multimodal sensing

Talented, international team tackling meaningful problems in remote patient monitoring

Transparent, mission-driven culture focused on continuous learning

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📌 Senior Applied Machine Learning Scientist (predictive analytics) (Quebec City)
🏢 The Toronto-Dominion Bank (Canada)
📍 Quebec City