Computer Vision/ML Engineer
Montreal, QC
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingDesign, 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
From the employer’s posting
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
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
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
Education & alternatives
What we look for: - Master's or PhD degree in Machine learning / Computer vision - Strong fundamentals: data structures, CV algorithms, and systems programming
Tools in this posting
- Python
- PyTorch
- C++
Source — Tool mentions in context
- 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
- 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
Benefits in the posting
Full benefits wording- High autonomy and technical ownership - you'll shape our computer vision architecture
- Work at the intersection of cutting-edge AI, edge computing, and healthcare
- Competitive salary
From the employer’s posting.
Job description
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 positionWe 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
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on norbert-health.breezy.hr. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Montreal, QC
- Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing - Talented, international team tackling meaningful problems in remote patient monitoring - Competitive salary
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 23, 2026
- Recorded sightings
- 50
- Last seen by us
- Oct 8, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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