AI Enginner
We are looking for a Video Analysis AI Engineer with a strong foundation across the complete software stack — from ingesting video streams to processing, analysing, and visualising results.
Key Responsibilities Video & Data Processing Building and maintaining video processing and analysis pipelines Work with live and file‑based video streams (IP video, encoded streams) Support computer vision / video analytics tasks such as detection, metadata extraction, tagging, and quality checks
Software Stack Development Develop and maintain backend services for video analysis workflows Work on AI based video analysis and Metadata development Work with APIs, data stores, and processing jobs supporting AI / ML based analytics outputs Assist in integrating analytics results with dashboards, logs, or reporting tools
Systems & Operations Help deploy and test applications in Linux-based and containerised environments Assist in debugging issues across the stack — ingestion, processing, storage, and outputs Support monitoring, logging, and performance analysis for live systems
Collaboration & Learning Work with Junior/Intern engineers to mentor production video systems Document implementations and learn best practices for scalable media platforms Participate in offshore team's technical work, code reviews and technical discussions
Required Skills & Qualifications Core Requirements Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field 3–5 years of experience in relevant field and technologies. 2+ years of hands-on working experience in Linux environments Hands-on experience in C, C++, Java and Python (mandatory) Strong working experience in backend frameworks, scripts, or microservices and databases (SQL and/or NoSQL) Exposure to video fundamentals (codecs, frames, resolution, bitrates) Strong knowledge of computer vision or video analytics concepts Familiarity with libraries such as OpenCV, FFmpeg, or similar is a plus Exposure to machine learning frameworks (PyTorch, TensorFlow, ONNX), containers (Docker) or cloud platforms Experience with real-time data or streaming systems