Face Deduplication Collection
Quick facts
- Type
- Part-time
- Location
- Remote
- Platform
- TELUS — 63 open jobs
- Apply
- Free to apply — never pay to get AI training work
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.
About TELUS
TELUS Digital (formerly TELUS International AI Data Solutions) is one of the longest-running employers of remote raters. Classic roles include search quality rater, map evaluator, ads evaluator and social media assessor, alongside newer AI response-evaluation projects.