Publié il y a 5 mois
Computer Vision/ML Engineer
@ Norbert Health
Montréal, Québec
En bref
Norbert Health is hiring a lead deep learning engineer to build computer vision models for its autonomous healthcare robots. The role covers real-time edge inference, model optimization for embedded hardware, and MLOps pipelines, with a focus on FDA-cleared contactless vital sign sensing. Strong C++ and Python skills and 5+ years deploying vision models to production are required, plus a Master's or PhD in machine learning or computer vision.
Responsabilités :
- Design, fine-tune and deploy computer vision models for real-time edge inference
- Optimize models for embedded deployment with quantization, pruning, TensorRT and Triton
- Build and maintain MLOps pipelines for training, validation and monitoring
- Develop video processing pipelines combining signal processing and ML vital sign extraction
- Set engineering best practices and shape the computer vision architecture
Résumé des exigences :
- Master's or PhD in machine learning or computer vision
- 5+ years deploying computer vision models to production
- Strong C++ for edge deployment pipeline
- Solid Python for ML experimentation and tooling
- Experience with PyTorch and model optimization for edge AI
- Ability to work independently and drive projects to completion
Outils et compétences
Source et dates
Site carrière / système de candidatures · breezy
- Date publiée par l’employeur
- 2026-06-21
- Première détection par notre source
- 2026-10-09
- Mise à jour du dossier source
- 2026-10-16
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Chef d’équipe |
| Domaine | Développement logiciel |
| Expérience | 5 an(s) et plus |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau, Laboratoire |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
| Formation | Maîtrise (exigé), Doctorat (exigé) |
| Domaines d’études | Machine learning, Computer vision |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Norbert Health
Profil d’entreprise sauvegardé
Renseignements historiques provenant d’un profil The Jobs API sauvegardé (champs LinkedIn/Crunchbase). Ils ne sont pas vérifiés en temps réel; les chiffres peuvent avoir changé. Les valeurs manquantes restent inconnues.
The AI module for autonomous care in the real world
Description complète de l’entreprise
Norbert is a physical and medical AI module that turns any robot into a health assistant — bringing care delivery to wherever patients are. Currently deployed in the real-world, and built for healthcare environments, Norbert enables robots to naturally interact with patients, measure vitals without contact, assess mobility and various behavioral signals, and share insights with care teams. By combining robotics, AI, and human-centered design, Norbert helps nurses and caregivers deliver safer, more preventive, and more personalized care. With no added staff or complex change management. We’re partnering with forward-thinking care providers to redefine how AI and robotics enhance care delivery and patient engagement.
- Abonnés LinkedIn
- 2 288
- Personnes associées sur LinkedIn
- 17
- Bureaux déclarés
- Brooklyn, NY, US
- Paris, FR
- Catégories d’activité
- Health Diagnostics
- Health Care
- Personal Health
- Autres noms enregistrés
- Norbert Health
- Le profil indique une agence de recrutement
- Non
- Investissement total déclaré
- 8 000 000
La devise et la date d’observation ne sont pas fournies; ce n’est ni une valorisation actuelle ni une ronde de financement.
Norbert is a physical and medical AI module that turns any robot into a health assistant — bringing care delivery to wherever patients are. Currently deployed in the real-world, and built for healthcare environments, Norbert enables robots to naturally interact with patients, measure vitals without contact, assess mobility and various behavioral signals, and share insights with care teams. By combining robotics…
| Champ | Valeur |
|---|---|
| Secteur | Wellness and Fitness Services |
| Taille | 11-50 employees |
| Siège social | Brooklyn, NY |
| Type d’organisation | Privately Held |
| Fondée en | 2019 |
| Offres sur Jobsy | 4 |
| Voir la page |
The company
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
- 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
Nice to haves:
- 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
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
- Competitive salary
- Transparent, mission-driven culture focused on continuous learning
Journal
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