Data Scientist- Computer Vision (Arabic Speakers)

Addenda; United Arab Emirates; On-site; AED 391,000 - 670,000; Full time

Job summary

Addenda is seeking an experienced Senior Data Scientist in the United Arab Emirates to lead the design, development, and deployment of vision-based AI systems. The role emphasizes traditional computer vision expertise, feature engineering, and modern deep learning, with hands-on work on agentic AI for autonomous decision-making.

You will drive scalable, production-grade vision solutions, oversee end-to-end workflows, and mentor teammates while collaborating with engineering, product, and

Qualifications

• 6–8 years in Data Science / Computer Vision / AI roles (B.Tech) or 4–6 years (M.Tech)
• Strong expertise in traditional computer vision and feature engineering
• Hands-on with deep learning for vision including segmentation
• Experience with agent-based AI systems and LLM integration

Responsibilities

• Design and develop end-to-end computer vision pipelines for real-world applications.
• Apply and optimize traditional computer vision algorithms including feature extraction and tracking.
• Develop and deploy deep learning models for instance and semantic segmentation.
• Build and integrate Agentic AI systems combining vision models with LLMs for intelligent workflows.
• Collaborate with cross-functional teams and mentor junior engineers.
• Lead model evaluation, experiments, and continuous improvement.

Skills

Python

Traditional computer vision

Feature engineering for vision tasks

Deep learning for vision

Agent-based AI systems

LLMs integration

Education

B.Tech / M.Tech in Data Science / AI or related field

Tools

PyTorch

TensorFlow

OpenCV

ONNX

Job description

We are looking for a highly skilled Senior Data Scientist specializing in Computer Vision to lead the design, development, and deployment of advanced vision-based AI systems. The ideal candidate will have deep expertise in traditional computer vision, feature engineering, and modern deep learning techniques, along with hands-on experience in building Agentic AI systems for intelligent decision-making.

You will play a key role in building scalable, production-grade vision solutions and driving innovation across AI-powered products.

Key Responsibilities

• Design and develop end-to-end computer vision pipelines for real-world applications.
• Apply and optimize traditional computer vision algorithms:
• Image processing, feature extraction, geometric transformations, tracking, and calibration
• Perform advanced feature engineering:
• Combine handcrafted features with deep learning embeddings
• Improve model performance through feature selection and transformation techniques
• Build and deploy deep learning models for:
• Instance and Semantic Segmentation
• Develop and integrate Agentic AI systems that:
• Enable autonomous reasoning and decision-making
• Integrate with external tools and APIs
• Optimize models for performance, scalability, and edge deployment.
• Lead model evaluation, experimentation, and continuous improvement.
• Collaborate with cross-functional teams across engineering, product, and business.
• Mentor junior team members and contribute to architectural decisions.

Required Skills & Qualifications

Experience

• Experience: 6–8 Years (B.Tech), 4-6 Years (M.Tech) in Data Science / Computer Vision / AI roles

Core Technical Skills

• Strong expertise in traditional computer vision:
• Strong experience in feature engineering for vision tasks
• Deep expertise in deep learning for vision:
• Object Detection, Semantic Segmentation, and Instance Segmentation
• Hands-on experience with:
• PyTorch / TensorFlow / OpenCV / Onnx
• Strong programming skills in Python

Agentic AI Expertise

• Experience in designing Agent-based AI systems using LLMs
• Familiarity with:
• Tool usage, planning, memory, and orchestration frameworks
• LangChain, AutoGen, or similar ecosystems
• Ability to combine vision models with LLMs for intelligent workflows

Preferred Qualifications

• Experience with Vision-Language Models (VLMs) and multimodal systems
• Knowledge of MLOps / model lifecycle management (MLflow, Azure ML, etc.)
• Experience in real-time or edge AI systems
• Domain experience in:
• Automotive, Insurance, Retail, Manufacturing, or Surveillance
• Familiarity with cloud platforms (Azure, AWS, GCP)