Computer Vision Engineer
Skills
About This Role
What you'll do
- Set the technical bar across our vehicle-detection and license-plate-recognition stack. Govern model architecture choices, dataset strategy, evaluation pipelines, and deployment patterns.
- Design, train, optimise, and deploy CV models for vehicle detection, classification (type, colour, brand, model), and GCC license-plate recognition.
- Convert and optimise models (YOLO family and others) for inference on Intel CPUs using OpenVINO; profile and reduce latency on edge hardware until you hit the SLA you own.
- Drive performance work on inference latency, model footprint, and CPU resource use for fleet-scale deployment.
- Govern the labelling guideline with the AI labelling operator: prioritise edge cases, audit dataset quality, sign off on dataset releases.
- Partner with the full-stack and web teams to expose model outputs through stable APIs that survive model updates.
- Mentor the AI labelling operator and any junior engineers who join later. Review code and model evaluations.
- Stay current on practical CV research; bring back what's worth integrating, reject what isn't.
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