Job Description

Roles & Responsibilities

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.

Desired Candidate Profile

What you'll bring

• 5+ years of production computer-vision work, including at least one role with senior or technical-lead responsibility.

• Deep C++ (C++17 or newer) and Python. Comfortable in both Linux and Windows build environments.

• Strong OpenVINO experience or equivalent (TensorRT, ONNX Runtime). You have personally optimised a model below an SLA you owned.

• ANPR / OCR / vehicle-recognition or comparable safety-critical CV background - ideally on edge hardware.

• Demonstrated ability to design model evaluation pipelines and ship measurable improvements over baselines.

• Linux command-line fluency.

• English fluency - written and spoken.

Nice to have

• Direct GCC license-plate experience.

• Experience working with classified or restricted-access datasets and the operational disciplines that go with them.

• Experience leading 1-3 person AI teams.

• C++ inference on Intel platforms (OpenVINO model optimisation, INT8 quantisation, multi-threaded inference).

• Windows desktop application packaging.

• Experience with M1 / Apple Silicon for future portability.

• Arabic - reading useful for GCC plate work.

Location & work authorization

Abu Dhabi - onsite at our headquarters. Open to candidates already in the UAE with valid work authorization, or to candidates willing to relocate; the company sponsors residency for international hires. Hybrid available after probation by manager agreement.