Face Deduplication Collection

TELUS Digital is seeking individuals for the Face Deduplication Collection project in Cambodia. This project aims to collect a diverse dataset of selfies and facial images to support machine-learning research and facial recognition model training.

The focus is on capturing real-world variations in lighting, poses, expressions, accessories, environments, and aging to improve model accuracy and robustness. Participants will contribute current neutral selfies, head-pose captures, and historical facial images.

Click here to apply and get started!

Company Overview

TELUS Digital crafts unique and enduring experiences for customers and employees, and creates future-focused digital transformations that stand the test of time. We are the brand behind the brands. Our global team members are both passionate ambassadors of our clients’ products and services, and visionary technology experts resolute in our pursuit to elevate their end customer journeys, solve business challenges, mitigate risks, and drive continuous innovation.

Our portfolio of end-to-end, integrated capabilities include digital IT services, such as cloud solutions and AI-fueled automation, trust and safety services, AI data solutions, including expertise in computer vision, and front-end digital design and consulting services. Fuel iX™ is TELUS Digital’s proprietary GenAI engine at the heart of our innovation, helping enterprises advance their GenAI pilots to working prototypes and production at scale, quickly, securely and responsibly across multiple environments, applications and clouds.

Powered by purpose, TELUS Digital leverages technology, human ingenuity and compassion to fuel remarkable outcomes and create inclusive, thriving communities in the regions where we operate around the world. Guided by our Humanity-in-the-loop principles, we take a responsible approach to the transformational technologies we develop and deploy by proactively considering and addressing the broader impacts of our work.

Quick Details

• Job Type: Part-time
• Experience: Entry level
• Qualifications: No specific education is needed to perform the project task.

Key Responsibilities

• Submit a minimum of 20 valid images to qualify for payment.
• Contribute current neutral selfies for identity references.
• Provide current head-pose captures to introduce pose variation.
• Submit historical images to capture natural aging and long-term appearance changes.
• Submit up to 30 images to help ensure enough images remain valid after review.

Requirements

• No specific education is needed to perform the project task.
• Ability to provide current neutral selfies.
• Willingness to capture head-pose variations.
• Access to historical photos for submission.
• Understanding of the importance of data diversity for machine learning.

Benefits

• Opportunity to contribute to machine-learning research and facial recognition model training.
• Potential for payment based on the number of accepted images.
• Be part of a project focused on real-world data variation.
• Engage with a company at the forefront of digital transformation.