Computer Vision Engineer

Polysense; Gent; Sur place; EUR 60 000 - 90 000; Plein temps

Résumé du poste

Polysense is seeking a Computer Vision Engineer in Gent, Belgium, to help transform visual data from food production lines into actionable insights. You will design vision setups, build robust architectures, and deploy models into customer environments.

The role combines hands-on development with deployment on factory floors, requiring strong Python, Linux, Docker and Kubernetes skills, plus a Master’s degree in CS/AI.

Qualifications

• Master's degree in CS/AI or related field.
• Proven experience with AI or computer vision projects.
• Strong programming experience in Python and production-ready code.
• Familiarity with Linux, Git, and container tools (Docker/Kubernetes).
• Ability to translate requirements into robust system designs.

Responsabilités

• Design vision setups (cameras, lighting, AI models) to detect differences between good and bad.
• Define system architecture, requirements, and risk assessments.
• Plan rollout and integrate product into customer environments.
• Validate and fine-tune performance in real conditions.
• Explain results to customers and ensure they receive full value.

Connaissances

Python

Linux

Git

Docker

Kubernetes

Computer Vision

AI

Documentation

Formation

Master's degree in CS/AI

Outils

Docker

Kubernetes

Description du poste

At Polysense, we help food producers see their process differently, quite literally. Our computer vision systems watch, analyze, and understand food production lines in real time, turning visual data into actionable insights. As a Computer Vision Engineer, you’ll help make that possible.

You’ll be part of the team that brings our systems to life, from the first design all the way to a running line on the factory floor. You’ll mix technical depth with practical problem-solving, and you’ll see your work make a tangible impact in the world of food manufacturing.

• You’ll start by understanding the customer’s world: their products, their process, and their challenges. Based on that, you’ll design the right vision setup: cameras, lighting, and AI models that can spot the difference between “good enough” and “perfect.”
• You’ll translate those insights into a solid system architecture. You’ll define requirements, assess risks, and make sure everything is ready before going live.
• From there, you’ll help plan and execute the rollout. Together with your team, you’ll integrate our product into the customer’s environment: training models, implementing vision pipelines, and making sure every component fits perfectly.
• Once deployed, you’ll validate and fine-tune performance. You’ll design validation strategies, analyze results, and keep iterating until the system performs flawlessly in real conditions.
• And because our customers are partners, not just clients, you’ll stay close to them — explaining results, solving issues, and ensuring they get the full value from what we deliver.
• You’re curious by nature and love solving real-world problems with technology. You probably hold a Master’s degree in Computer Science, Artificial Intelligence, or something close to it, but what really defines you is how you think, build, and learn.
• You’ve worked on AI or computer vision projects before and know what it takes to bring models from a lab setting into production. Python feels like home, and you’re comfortable navigating Linux, Git, and container tools like Docker or Kubernetes.
• You like structure and clear documentation. Not because someone told you to, but because it helps your team move faster and stay aligned. You’re pragmatic when it counts, and analytical when it matters.
• You stay up to date with what’s new in AI and machine learning, not out of obligation, but because you’re genuinely fascinated by where the field is heading. You want to use that knowledge to make an impact: improving how food is made, reducing waste, and helping the planet along the way.
• You’re open-minded, honest, and collaborative. You like to learn from others and share what you’ve learned in return. You’re flexible, ambitious, and ready to grow with a team that’s building something meaningful together.