Data Scientist- Computer Vision (Arabic Speakers)

Role Overview

Key Responsibilities

• Design and develop end-to-end computer vision pipelines.
• Apply traditional computer vision algorithms for image processing, feature extraction, tracking, and calibration.
• Perform feature engineering using visual features, handcrafted features, and deep learning embeddings.
• Build and deploy object detection, instance segmentation, and semantic segmentation models.
• Develop agentic AI systems for autonomous reasoning, workflow orchestration, and tool integration.
• Optimize models for performance, scalability, and edge deployment.
• Lead model evaluation, experimentation, and continuous improvement.
• Collaborate across engineering, product, and business teams.
• Mentor junior team members and contribute to architecture decisions.

Experience Requirements

• Six to eight years of experience with a B.Tech, or four to six years with an M.Tech, in Data Science, Computer Vision, or AI roles.
• Strong expertise in traditional computer vision and feature engineering for vision tasks.
• Deep expertise in object detection, semantic segmentation, and instance segmentation.
• Strong Python programming skills.
• Hands-on experience with PyTorch, TensorFlow, OpenCV, and ONNX.

Agentic AI Expertise

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

Preferred Qualifications

• Experience with Vision-Language Models and multimodal systems.
• Knowledge of MLOps or model lifecycle management, including MLflow or Azure ML.
• Experience with real-time or edge AI systems.
• Domain experience in automotive, insurance, retail, manufacturing, or surveillance.
• Familiarity with Azure, AWS, or GCP.