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 but growing 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 roleClose collaboration with our CTO, engineering team and hospital partnersHigh ownership over core computer vision components, from model design to deploymentRegular visits to partner hospitals for observation, testing and validationFlexible working setup (Antwerp office + remote)Your mission ahead
Perception & tracking
Develop and optimise detection, segmentation and tracking models for complex operating room environmentsImprove accuracy under challenging conditions, including occlusions, partial visibility and dynamic scenesBuild reliable vision pipelines that work consistently across procedures and hospital settingsTraining & model quality
Build reproducible training and evaluation pipelinesDevelop visual recognition methods for challenging objectsAnalyse failure modes and improve model accuracy across procedures and hospital environmentsEdge deployment & robustness
Optimise and deploy vision components on edge devicesBalance accuracy, latency and robustness under real-world constraintsMonitor and validate model performance in deployed systemsClinical validation & integration
Observe procedures and test directly in partner hospitalsTranslate practical observations into improvements to models and pipelinesCollaborate with our team to improve overall system accuracy and reliabilityIntegrate 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 experienceStrong proficiency in Python and common computer vision frameworks (e.g. PyTorch, OpenCV or similar)Hands-on experience building and evaluating computer vision models and pipelinesExperience working with detection, segmentation, tracking or visual recognition systemsFamiliarity with Linux environments and Docker-based workflowsAbility to write clear, structured and maintainable codeExperience working with Git and collaborative workflows (pull requests, issues)Clear communication skills and a willingness to work directly with hospital staffExperience with deploying and optimising vision models on edge hardwareNice to have
Experience with multi-camera visionExperience with the NVIDIA ecosystemFamiliarity with production model monitoring and CI/CD pipelines for ML or vision systemsExperience working with privacy-sensitive or regulated environmentsQuick 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) in a mission-driven healthtech startupDirect ownership over key parts of our computer vision and AI stackCompetitive salary and additional benefits, aligned with your experienceSmall team, short feedback loops, high autonomyFlexible working setup (Antwerp office, up to 2 days remote)Building software that’s used in real hospitalsWe would love to hear from you! Please send us your CV and a few lines about what caught your interest. 📨 Contact us
