Computer Vision Engineer
Lynqo
Software Engineering
Posted on Feb 3, 2026
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Computer Vision Engineer
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Operating rooms are visually complex, dynamic environments with strict reliability and privacy requirements. This role sits at the intersection of raw camera data, computer vision models, and clinical workflows — turning challenging visual input into robust, deployable perception that works in real surgical settings.
Working at Lynqo
We build a software platform that is used in real hospital environments, with real constraints and real users. That means clarity, reliability and good communication matter just as much as technical elegance.
We value ownership, curiosity and openness. People at Lynqo take responsibility for their work from idea to deployment, invest time in understanding the context they’re building for, and aren’t afraid to ask questions or challenge assumptions.
We’re a small team with short feedback loops. You’ll work closely with both technical and non-technical colleagues, and your input will shape how the product evolves.
Your role in a nutshell
Full-time role, open to discuss a part-time arrangement
Close collaboration with our CTO, AI engineer and hospital partners
High ownership over core computer vision components, from model design to deployment
Direct impact on real hospital workflows
Flexible working setup (Antwerp office + remote)
Your mission ahead
Scene understanding & tracking
Design and implement detection and tracking models for critical objects and regions in the OR
Build and maintain pipelines that track scene elements across time
Handle occlusions, partial visibility and dynamic scenes typical of surgical environments
Implement privacy-aware vision components as part of the perception pipeline
Edge deployment & robustness
Optimise and deploy vision components on edge devices
Balance accuracy, latency and robustness under real-world constraints
Monitor and improve runtime performance and system stability
Clinical validation & integration
Test and iterate directly in pilot hospitals
Analyse failure modes and improve system behaviour based on actual usage
Integrate vision components cleanly into the broader Lynqo platform
✅ This role is a great fit if you have …
2+ years of professional experience in computer vision, applied machine learning or a related field, or equivalent practical experience
Strong proficiency in Python and common computer vision frameworks (e.g. PyTorch, OpenCV or similar)
Hands-on experience building and deploying computer vision models and pipelines
Experience working with detection, tracking or scene understanding systems
Familiarity with Linux environments and Docker-based workflows
Ability to write clear, structured and maintainable code
Experience working with Git and collaborative workflows (pull requests, issues)
Nice to have
Experience deploying vision models on edge devices
Experience working with privacy-sensitive or regulated environments
Familiarity with CI/CD pipelines for ML or vision systems
Quick mindset check
🔲 You take responsibility from implementation through deployment
🔲 You communicate clearly with both technical and non-technical stakeholders
🔲 You invest time in understanding real-world constraints
🔲 You prioritise clarity, correctness and maintainability over unnecessary complexity
What’s in it for you?
Full-time role (employee or freelance) in a mission-driven healthtech startup
Direct ownership over key parts of our computer vision and AI stack
Competitive salary and additional benefits, aligned with your experience
Small team, short feedback loops, high autonomy
Flexible working setup (Antwerp office, up to 2 days remote)
Building software that’s used in real hospitals
We would love to hear from you! Please send us your CV and a few lines about what caught your interest. 📨 Contact us