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:
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.
Compensation and Benefits
Why you should apply for this position today
This project offers a unique opportunity to contribute to impactful machine-learning research. By participating, you can help improve facial recognition technologies while earning compensation for your contributions.
Skills
Responsibilities
Qualifications
Education Requirements
Education Requirements Credential Category
Experience Requirements
Why work in Calliaqua
Calliaqua offers a beautiful coastal environment with a rich cultural heritage. Living in this area provides opportunities for outdoor activities, community engagement, and a relaxed lifestyle, making it an excellent place to balance work and leisure.
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