Selfie data collection - Netherlands
Key Skills
Job Description
Job description The objective of this project is to collect a large and diverse dataset of current neutral selfies, head-pose captures, and historical facial images to support machine-learning research and facial recognition model training at TELUS. The focus is on capturing real-world variation across lighting, poses, expressions, accessories, environments, and aging to improve model accuracy and robustness. The collection includes: • Current Neutral Selfies – clean frontal selfies serving as high-quality identity references, with natural variation in appearance and surroundings. • Current Head-Pose Captures – selfies captured in assigned head directions to introduce pose variation. • Historical Images – older photos from participants’ galleries to capture natural aging and long-term appearance changes. How to Apply Visit our AI Community portal: https://www.telusinternational.ai/cmp/contributor/jobs/available/128816 Create or update your profile Upload your resume Apply for the role – That’s it! Qualification path No specific education is needed to perform the project task.
Core Responsibilities
Collect current neutral selfies, selfies in assigned head directions, and historical facial images from participants’ photo galleries. Provide a diverse set of images reflecting real-world variation in lighting, poses, expressions, accessories, environments, and aging for machine-learning research and facial recognition model training.
Requirements
No specific education is required. The posting does not state any other qualifications or experience requirements.
About TELUS Digital
Industry: IT Services and IT Consulting
Company size: 10,001+ employees
TELUS Digital is a premier global technology services provider. We help the world's biggest brands win the moments that matter, for their customers and their business. Our teams design and operate the AI-powered experiences customers rely on across web, mobile, conversational AI, and human agents. Across the AI lifecycle, we supply the data that trains frontier models, and we build, run, and protect AI for enterprises and for ourselves, at scale, every day. Guided by our Humanity-in-the-Loop principles, our 80,000+ team members deliver for 600+ clients in over 35 countries.