AI Data Annotation Analyst – Identity Verification

About the role

We are looking for an AI Data Annotation Analyst to support the development of secure and fair identity verification systems. You will work with a collaborative engineering team to label and validate diverse datasets that power document fraud detection, deep‑fake detection, presentation‑attack detection and face‑recognition models.

Key responsibilities

• Annotate data across documents, images, video and audio following detailed guidelines.
• Identify and label document elements such as names, photos, signatures and holograms, and flag signs of tampering.
• Mark manipulated regions in deep‑fake and image‑tamper datasets.
• Tag liveness indicators and spoof artifacts for presentation‑attack detection.
• Draw bounding boxes, facial landmarks and expression labels for face‑recognition tasks.
• Apply frame‑level labels in video for PAD and deep‑fake detection.
• Document edge cases, suggest guideline improvements and review peer annotations for consistency.
• Collaborate with ML engineers and data scientists to enhance dataset quality and annotation tools.

Required profile

• Strong attention to detail and ability to maintain accuracy on repetitive tasks.
• Clear written and verbal communication to describe edge cases.
• Basic understanding of computer‑vision and machine‑learning concepts (training provided).
• Comfort with web‑based annotation platforms (training provided).

Required skills

• Computer vision
• Machine learning
• Web‑based annotation tools

What we offer

• Opportunity to contribute to cutting‑edge identity verification technology.
• Collaborative environment with continuous learning and knowledge sharing.