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Chief Video Analytics Specialist
2 weeks ago
This role is designed to lead the development of AI-powered video analytics solutions. The ideal candidate will have expertise in fine-tuning AI models, deploying computer vision systems on CPU and GPU servers, and integrating end-to-end CCTV systems with RTSP streams.
Key Responsibilities:
- Develop and fine-tune AI and computer vision models for video analytics applications, including object detection, tracking, anomaly detection, and behavioral analysis in CCTV feeds.
- Deploy computer vision systems on CPU and GPU servers, optimizing for performance, scalability, and resource efficiency in production environments.
- Design and implement end-to-end CCTV system integrations, handling RTSP stream inputs, video decoding outputs, and embedding CV/AI/VA engines for real-time processing.
- Collaborate on client-server architectures, ensuring robust communication between CCTV cameras, servers, and networked devices.
- Optimize AI models for low-latency inference on edge devices or cloud servers, focusing on CCTV-specific use cases like security monitoring and video surveillance.
- Troubleshoot and debug issues related to video streams, network connectivity, and system performance.
- Conduct testing, validation, and deployment of AI solutions, ensuring compliance with industry standards for data privacy and security.
- Stay updated on emerging computer vision and AI technologies, contributing to R&D initiatives for next-gen video analytics.
Required Qualifications and Skills:
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field, with a strong focus on computer vision.
- 3+ years of professional experience in AI engineering, specifically in computer vision and AI model fine-tuning (e.g., using frameworks like TensorFlow, PyTorch, or OpenCV).
- Proficiency in programming languages such as Python or C/C++, with hands-on experience in developing and optimizing computer vision algorithms.
- Proven track record in deploying computer vision systems on CPU and GPU servers (e.g., using CUDA, TensorRT, or ONNX for acceleration).
- Experience with CCTV video analytics (VA) applications, including processing real-time video streams for security and surveillance.
- Demonstrated expertise in end-to-end CCTV system integration, including RTSP stream handling, video encoding/decoding, and integrating CV/AI/VA as core engines.
- Solid understanding of client-server architectures, CCTV camera systems, internet networks, and protocols (e.g., TCP/IP, ONVIF).
- Strong problem-solving skills and the ability to work independently or in a team.
Benefits:
- Flexible working hours.
- Gain hands-on experience in a leading AI company at the forefront of technological advancements.
- Potential for performance-based incentives and company shares.
