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# Computer Vision Engineer

- **Company:** UUG AI
- **Location:** Gent, Belgium
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Computer Vision, C++ (Programming Language), Computer Clusters, Nvidia CUDA, Data Files, Software Debugging, Monitoring of Systems, Python (Programming Language), OpenCV, Management of Software Versions, Pytorch, Model Validation, Machine Learning Operations, Front End Software Development, TensorRT, Multiaccess Edge Computing
- **Published:** October 29, 2026
- **Apply:** https://www.vdab.be/vindeenjob/vacatures/74927871

## About the Role

Full-time position with hybrid collaboration from Ghent. Work on production computer vision for varied environments, constrained edge hardware and GPU-backed inference. Collaborate with product and engineering colleagues and grow ownership from problem definition through deployment, monitoring and iteration.

## Description

UUG.AI turns camera streams into useful, real-time signals for operations teams. As a Computer Vision Engineer, you work across the model lifecycle: from framing a problem and preparing data to evaluating, deploying and observing models in production.

Your responsibilities:

 - Build and improve detection, segmentation, classification and multi-object tracking pipelines.

 - Define datasets, evaluation sets and metrics reflecting real customer operating conditions.

 - Optimise inference for edge devices and GPU clusters, balancing accuracy, latency and cost.

 - Package and serve models through our inference stack, including NVIDIA Triton where appropriate.

 - Investigate failures using recordings, telemetry and user feedback.

 - Collaborate with platform, workflow and frontend engineers to make model output actionable.

This is a full-time engineering role, with hybrid collaboration from Ghent, Belgium.

Hands-on experience building computer vision systems with Python and PyTorch or a comparable framework. Understanding of model evaluation and representative test sets. Comfortable with video, OpenCV, image processing and production-inference trade-offs. Able to work with tests, containers, APIs, profiling and operational debugging. Clear communication and ownership with support from the team.

Helpful, not all required: YOLO, tracking or segmentation; Triton, CUDA or TensorRT; MLOps, model monitoring and dataset versioning; camera protocols and edge computing; Go or C++. Relevant skills and practical experience matter; no mandatory diploma or fixed number of years.

Fasen en procedures van de technische en functionele tests van informaticaprogramma's en -applicaties bepalen en uitvoeren (planning, validatie, ...)