Quantitative Developer jobs in United Arab Emirates

JOB SUMMARY: We are seeking an experienced Computer Vision Engineer with a strong background in AI and Large Language Models (LLMs). The ideal candidate will design build and deploy computer vision solutions that integrate with generative AI and LLM frameworks to interpret analyze and describe visual data. This role bridges the gap between image understanding and natural language processing enabling intelligent visual-language applications.

• Develop and implement computer vision models for image classification object detection segmentation facial recognition and visual understanding.
• Integrate vision models with LLMs (e.g. GPT LLaVA CLIP or multimodal models) to build systems that interpret and describe visual content.
• Design AI pipelines that combine text images and video data for multimodal learning and reasoning.
• Utilize deep learning frameworks (TensorFlow PyTorch OpenCV) to prototype and deploy models.
• Collaborate with data scientists and AI researchers to fine-tune vision-language models for specific tasks such as visual QA captioning or scene analysis.
• Implement data preprocessing augmentation and annotation pipelines for large-scale image datasets.
• Conduct performance benchmarking optimization and deployment of models in production environments.
• Research and experiment with emerging techniques in Generative AI multimodal transformers and neural architecture optimization.
• Develop APIs and tools for internal teams to utilize vision LLM capabilities.
• Ensure compliance with ethical AI practices including bias mitigation and data privacy.

• Bachelors or Masters degree in Computer Science AI Computer Vision or related field (PhD preferred).
• 3-7 years of experience in computer vision deep learning or multimodal AI.
• Strong proficiency in Python and frameworks such as PyTorch TensorFlow Keras and OpenCV.
• Experience integrating LLMs (GPT Claude Gemini or open-source models) with vision systems.
• Solid understanding of transformer architectures CNNs diffusion models and attention mechanisms.
• Familiarity with multimodal datasets (COCO Visual Genome etc.) and evaluation metrics for vision tasks.
• Experience with cloud-based AI tools (Azure AI AWS Sagemaker Google Vertex AI etc.).
• Ability to write clean scalable and production-grade code.
• Strong analytical problem-solving and communication skills.

• Experience with multimodal LLM frameworks such as CLIP BLIP LLaVA or Kosmos-2.
• Background in natural language processing and prompt engineering.
• Hands-on experience with edge deployment (NVIDIA Jetson OpenVINO ONNX).
• Knowledge of reinforcement learning generative models or 3D vision.
• Publications or open-source contributions in AI research are a plus.