JOB DESCRIPTION:

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.

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 (CV).
• 3+ years of professional 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.

• Develop and fine-tune AI and CV models for video analytics applications, including object detection, tracking, anomaly detection, and behavioural 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.