Computer Vision Engineer

Job Title: Computer Vision Engineer

We are seeking a highly skilled Computer Vision Engineer to join our team and contribute to a live, production-grade vision system. The role focuses on developing, optimizing, and maintaining computer vision models and real-time video processing pipelines integrated into a Python-based backend environment.

Key Responsibilities:

• Develop, train, and optimize computer vision models for real-world applications
• Fine-tune models based on new datasets and evolving system requirements
• Build and maintain real-time video processing pipelines (ingestion, decoding, streaming)
• Integrate computer vision models into Python-based backend systems
• Work on object detection, tracking, and ROI (Region of Interest) optimization
• Optimize performance using GPU acceleration (NVIDIA CUDA)
• Maintain and improve existing G Streamer-based video pipelines
• Support deployment in on-premise environments and production systems
• Ensure system stability, scalability, and performance in live conditions

Requirements:

• Strong experience in Python backend development
• Solid understanding of Computer Vision and Deep Learning concepts
• Hands-on experience in model training and fine-tuning
• Experience with real-time video processing and streaming systems
• Strong knowledge of object detection and tracking algorithms
• Experience with NVIDIA CUDA or GPU acceleration frameworks
• Familiarity with GStreamer or similar multimedia frameworks
• Ability to work on production-level AI systems
• Experience with on-premise AI deployments
• End-to-end CV pipeline experience (data collection → training → deployment → monitoring)
• Knowledge of performance optimization in real-time systems

Pay: AED7,000.00 - AED8,000.00 per month

Application Question(s):

• How have you designed or optimized a real-time computer vision pipeline in production?
• What techniques do you use to improve model performance (accuracy vs speed trade-off) in real-time systems?
• Can you explain your experience with object detection and tracking models in live video streams?
• How do you handle GPU optimization and reduce inference latency using CUDA or similar tools?
• Describe a full computer vision project you have worked on from data preparation to deployment and monitoring.

Work Location: In person