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About the Role
This role owns the AI match analysis platform end-to-end, focusing on improving live sports models and building a new product on the same foundations. You will ship to a live product from week one, raising accuracy on sports models while architecting the second industry's deployment. Responsibilities include model selection, training strategy, dataset operations, evaluation methodology, and technical leadership.
Responsibilities
- Own the shared CV platform, end to end: camera ingestion, detection and tracking, OCR, classification, and the reporting pipeline.
- Ship to a live product from week one, raising accuracy on sports models with real users.
- Architect the second industry's deployment on the same stack.
- Manage architecture: model selection and training strategy, annotation and dataset operations, evaluation methodology, the on-prem/cloud split.
- Ship the new industry's first deployments, then harden both products as one platform.
- Provide technical leadership of the engineering team.
Requirements
- 5+ years building computer vision systems that ran in production.
- Deployed systems with users, not notebooks.
- Strong Python and PyTorch.
- Hands-on with modern detection and tracking (YOLO family, ByteTrack/DeepSORT or similar).
- Video pipeline experience: RTSP/IP cameras, scheduled or streaming inference, ffmpeg-level fluency.
- Experience building datasets, running annotation operations, and measuring models honestly against ground truth.
- Experience fine-tuning open-source models (detection, OCR of the PaddleOCR/TrOCR class) and replacing them with own models trained on validated annotations, with a working annotation-review loop.
- Fluent in the modern CV tooling ecosystem: Roboflow or equivalent for dataset and annotation operations, experiment tracking, model registries.
- Ownership temperament: take a vague operational goal and return a working system without waiting for a spec.
Skills
- Computer Vision
- Python
- PyTorch
- Object Detection
- Object Tracking
- YOLO
- ByteTrack
- DeepSORT
- Video Pipelines
- RTSP
- IP Cameras
- Streaming Inference
- FFmpeg
- Dataset Building
- Annotation Operations
- Model Evaluation
- Model Fine-tuning
- OCR
- PaddleOCR
- TrOCR
- Roboflow
- Experiment Tracking
- Model Registries
- OCR
- Action Recognition
- Pose Estimation
- Edge Deployment
- Jetson
- Inference Cost Engineering
- Camera Systems
- IoT
- Sensor Selection
- Lens Selection
- PoE Networking
- ONVIF
- NVRs
- Weatherproof Housings
Location
- Remote
- Dubai
Work Type
- Full-time
- Remote friendly
Experience Level
- 5+ years
Benefits
- Competitive package
- Options
About the Company
- Our client does AI match analysis for youth football using fixed cameras to record sessions.
- Models detect events, track players, and read jersey numbers from low-res footage.
- Academies and parents receive match stats, highlights, and per-player records.
- The system is currently operational at a pilot academy in Dubai with paying clients.
- The company is expanding this technology stack into a second industry with committed first customers.