Role Overview
We are looking for a Junior Video Analysis Engineer with a strong foundation across the complete software stack - from ingesting video streams to processing, analysing, and visualising results.
This role is ideal for fresh graduates or early‑career engineers who enjoy working with video, data, and real‑time systems, and want hands‑on exposure to production deployments.
You will work closely with senior engineers on video ingestion, analytics pipelines, backend services, and operational tooling.
Key Responsibilities
Video & Data Processing
- Assist in building and maintaining video processing and analysis pipelines
- Work with live and file‑based video streams (IP video, encoded streams)
- Support basic 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 senior engineers to understand production video systems
- Document implementations and learn best practices for scalable media platforms
- Participate in code reviews and technical discussions
Required Skills & Qualifications
Core Requirements
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
- 0-2 years of experience (or strong academic / project background)
- Solid understanding of software engineering fundamentals
- Comfortable working in Linux environments
Programming & Tools
- Proficiency in Python (mandatory)
- Familiarity with backend frameworks, scripts, or microservices
- Basic understanding of databases (SQL and/or NoSQL)
Video & Analytics Foundations
- Exposure to video fundamentals (codecs, frames, resolution, bitrates)
- Basic knowledge of computer vision or video analytics concepts
- Familiarity with libraries such as OpenCV, FFmpeg, or similar is a plus
Good to Have (Not Mandatory)
- Exposure to machine learning frameworks (PyTorch, TensorFlow, ONNX)
- Knowledge of containers (Docker) or cloud platforms
- Experience with real-time data or streaming systems
- GitHub projects, internships, or academic projects involving video or AI
What You'll Gain
- Hands-on experience with real-world video analytics systems
- Exposure to broadcast, streaming, and large-scale IP video deployments
- Mentorship from senior engineers in media and AI systems
- Opportunity to grow into AI Engineer / Platform Engineer roles
Why Join Digital Roundabout
- Work on production systems, not toy problems
- Flat hierarchy and strong learning culture
- Exposure to cutting-edge video and media technology
- Clear growth path for early‑career engineers
