Computer Vision Engineer
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About the Role
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.
Key Skills for This Role
Full Job Posting
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.
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