Overview

Data Science Lead Jobs in Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates at 99brightminds

Title: Data Science Lead

Company: 99brightminds

Location: Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates

Data Science Lead

EXPERIENCE: 10 – 15 YEARS

 

Position Summary

As Data Science Lead, you will set the technical direction for AIQ's computer-vision research and own the quality of the models that power our video-analytics platform. You will lead a team of data scientists and ML engineers from problem framing through to production and monitoring, while shaping solution architecture and communicating outcomes to stakeholders.

 

Responsibilities

  • Lead the design and development of computer-vision solutions across object detection, tracking, re-identification, action recognition, and segmentation.
  • Drive model selection and experimentation with YOLO, Transformer-based / ViT architectures, and RF-DETR.
  • Apply and guide the use of Vision-Language Models (VLMs), including fine-tuning for computer-vision tasks.
  • Own model optimisation for production (TensorRT, ONNX, OpenVINO), accounting for edge-AI deployment constraints (latency, FPS, GPU limits).
  • Architect and oversee multi-camera tracking and video-analytics systems.
  • Own the MLOps lifecycle end to end — _training, deployment, and monitoring.
  • Lead, mentor, and conduct code reviews for a team of data scientists and engineers.
  • Contribute to solution architecture and communicate technical direction and outcomes to stakeholders.

 

Qualifications

  • Bachelor's or Master's degree (PhD a plus) in Computer Science, Machine Learning, Data Science, or a related field.
  • 10 – 15 years of applied machine-learning experience, with deep expertise in computer vision.
  • Strong Python, with hands-on PyTorch / TensorFlow.
  • Hands-on experience with YOLO, Transformer-based / ViT architectures, and RF-DETR.
  • Experience with Vision-Language Models (VLMs) and fine-tuning for CV tasks.
  • Proven model-optimisation experience (TensorRT, ONNX, OpenVINO) and understanding of edge-AI deployment constraints (latency, FPS, GPU limits).
  • Experience building multi-camera tracking and video-analytics systems.
  • Command of the full MLOps lifecycle (training → deployment → monitoring).
  • Demonstrated team leadership, code review, and mentoring.
  • Strong stakeholder-communication and solution-architecture skills

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