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.
To qualify for payment, you must submit a minimum of 20 valid images. The maximum payout is based on 24 accepted images. Due to the strict automated and manual Quality Control (QC) process, we strongly recommend submitting 30 images to help ensure that enough images remain valid after review.
Participants can earn a total of $13.20 USD upon successfully completing the project requirements.
Equal Opportunity
All qualified applicants will receive consideration for a contractual relationship without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. At TELUS Digital AI, we are proud to offer equal opportunities and are committed to creating a diverse and inclusive community. All aspects of selection are based on applicants’ qualifications, merits, competence, and performance without regard to any characteristic related to diversity.
To apply, please reach me at < email deleted for security reasons > by sending a copy of your CV along with the following details:
Subject: [University Name] - [Job Post Title]
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