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Computer Vision Engineer Jobs in Quebec (NOW HIRING)

Motorola

Director of Computer Vision

Quebec, QC · On-site

The Director of Computer Vision will drive the technical vision, research and engineering execution ... Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to ...

Jumio

Senior Machine Learning Engineer

Montreal, QC

We're looking for a Senior Machine Learning Engineer with strong computer vision expertise to join our Biometrics team. You'll ramp up on the biometrics domain while contributing to the design ...

Norbert Health

Applied AI Engineer

Montreal, QC · On-site

Partner with the algorithms team (signal processing, computer vision) on integration with their lower-level pipelines What we're looking for * BS in Computer Science, Engineering, or a related field ...

Norbert Health

Applied AI Engineer

Montreal, QC

Partner with the algorithms team (signal processing, computer vision) on integration with their lower-level pipelines What we're looking for * BS in Computer Science, Engineering, or a related field ...

Jestais

Engineer advanced features including promotions, seasonality, holidays, stockouts, lag variables ... Computer Vision * Develop and deploy computer vision solutions for product classification, visual ...

Jesta I.S.

Engineer advanced features including promotions, seasonality, holidays, stockouts, lag variables ... Computer VisionDevelop and deploy computer vision solutions for product classification, visual ...

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Computer Vision Engineer information

What do computer vision engineers do?

Computer vision engineers develop algorithms and models that enable computers to interpret and analyze visual data such as images and videos. They often work with machine learning frameworks, programming languages like Python or C++, and tools such as OpenCV or TensorFlow to create applications in areas like object detection, facial recognition, and autonomous systems.

What engineers make $300,000 a year?

Senior computer vision engineers, especially those with advanced skills in deep learning, machine learning, and experience with tools like TensorFlow or PyTorch, can earn $300,000 or more annually in high-demand industries such as technology, autonomous vehicles, or AI research. Compensation often depends on experience, location, and company size, with some roles in Silicon Valley or major tech firms reaching this level through base salary, bonuses, and stock options.

What are Computer Vision Engineers?

Computer Vision Engineers are professionals who develop algorithms and systems that enable computers to interpret and process visual information from the world, such as images and videos. They work on tasks like object detection, facial recognition, image segmentation, and more, often using machine learning and deep learning techniques. These engineers apply their expertise in fields like robotics, autonomous vehicles, healthcare, and augmented reality, turning raw visual data into actionable insights.

What is the difference between Computer Vision Engineer vs Machine Learning Engineer?

AspectComputer Vision EngineerMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, Electrical Engineering, or related; knowledge of image processing and computer vision librariesBachelor's or Master's in CS, Data Science, or related; strong programming and statistical skills
Work EnvironmentDevelops algorithms for image/video analysis, object detection, and recognition in tech, automotive, or healthcare industriesBuilds models for various data types, including text, images, and structured data across multiple sectors
Employer & Industry UsageTech companies, autonomous vehicles, robotics, healthcareTech firms, finance, e-commerce, healthcare, and research institutions

While both roles involve machine learning techniques, Computer Vision Engineers specialize in developing algorithms for visual data, whereas Machine Learning Engineers work on broader data modeling across various data types. The roles often overlap but differ mainly in focus and application areas.

What are the key skills and qualifications needed to thrive as a Computer Vision Engineer, and why are they important?

To thrive as a Computer Vision Engineer, you need a strong background in computer science, mathematics, and machine learning, often supported by a relevant degree and experience with image processing algorithms. Familiarity with tools and frameworks such as OpenCV, TensorFlow, PyTorch, and proficiency in programming languages like Python or C++ is essential, along with knowledge of deep learning techniques. Analytical thinking, creativity, and effective communication are standout soft skills for this role. These skills and qualities are crucial for developing innovative vision solutions, interpreting complex data, and collaborating efficiently within interdisciplinary teams.

What engineer makes $500,000 a year?

A senior computer vision engineer at top tech companies or in specialized industries can earn $500,000 or more annually, often including bonuses and stock options. These roles typically require advanced skills in machine learning, deep learning, and experience with tools like TensorFlow or PyTorch, along with a strong educational background and years of experience. Compensation varies based on location, company size, and individual expertise.

What Does a Computer Vision Engineer Do?

Computer vision is a branch of artificial intelligence that attempts to replicate human analytical processes by using algorithms and computer models to understand and identify patterns in images. As a computer vision engineer, you use software to handle the processing and analysis of large data populations, and your efforts support the automation of predictive decision-making efforts. Your responsibilities involve research, programming, data analysis, and user interface design. You may work on a variety of exciting development projects like self-driving cars, mobile devices, innovative features and capabilities in sports and entertainment, and the next generation of social media enhancements.

What are some common challenges faced by Computer Vision Engineers when deploying models to production environments?

Computer Vision Engineers often encounter challenges such as ensuring model accuracy in diverse real-world conditions, optimizing models for efficiency on edge devices, and handling large-scale data processing. Deploying models to production requires balancing performance with resource constraints and addressing issues like latency, scalability, and data privacy. Collaborating closely with software engineers and data scientists is crucial to integrate solutions effectively and continuously monitor and improve model performance in live applications.

Will AI replace computer vision engineers?

AI is transforming the field of computer vision, but computer vision engineers are essential for developing, training, and maintaining AI models and systems. Their expertise in algorithms, programming, and domain knowledge ensures the effective application of AI in real-world scenarios, making complete replacement unlikely in the near term.
More about Computer Vision Engineer jobs
What job categories do people searching Computer Vision Engineer jobs in Quebec look for? The top searched job categories for Computer Vision Engineer jobs in Quebec are:
Computer Vision Engineer jobs near you
Infographic showing various Computer Vision Engineer job openings in Quebec as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution.
Computer Vision/ML Engineer

Computer Vision/ML Engineer

Norbert Health

Montreal, QC • On-site

Full-time

Posted 28 days ago

Job description

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 memberrounding 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