We are seeking a talented AI Engineer with a strong background in Computer Vision (CV) to design, develop, and deploy AI-powered video analytics (VA) solutions, particularly for CCTV applications. The ideal candidate will have expertise in fine-tuning AI models, deploying CV systems on CPU and GPU servers, and integrating end-to-end CCTV systems with RTSP streams. You will collaborate with cross-functional teams to build scalable, efficient solutions that process video feeds, perform real-time analytics, and ensure seamless integration with client-server architectures and network infrastructures. If you thrive in a fast-paced environment and have hands-on experience with CCTV hardware and networks, this role offers an exciting opportunity to drive innovation in surveillance technology.
- Develop and fine-tune AI and CV models for video analytics applications, including object detection, tracking, anomaly detection, and behavioral analysis in CCTV feeds.
- Deploy CV 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 CV and AI technologies, contributing to R&D initiatives for next-gen video analytics.
Job Requirements:
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field, with a strong focus on Computer Vision (CV).
- Experience in AI engineering, specifically in CV 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 CV algorithms.
- Proven track record in deploying CV 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., HTTP, TCP/IP, ONVIF).
- Strong problem-solving skills and the ability to work independently or in a team.
Preferred Skills and Advantages:
- Hands-on experience with CCTV hardware integration, network troubleshooting, and optimizing for edge computing in surveillance environments.
- Familiarity with cloud platforms (e.g., AWS, Azure) for scalable AI deployments.
- Knowledge of related tools like FFmpeg for video processing, Docker/Kubernetes for containerization, or edge AI frameworks.
- Experience in agile development methodologies and version control (e.g., Git).
- Prior work in security or video analytics industries is a plus.
- Excellent communication skills for collaborating with non-technical stakeholders.