Antony M.

Key Skills

Software

Don't disclose

Other

Top Subject Matter

Egocentric human motion / activity recognition datasets

AI training / RLHF and data annotation workforce qualification

Legal Services & Contract Review

Top Data Types

Video

Image

Text

Document

Top Task Types

Action Recognition

Data Collection

Freelancer Overview

Egocentric Video Data Collector (Human Motion Data Workers). Brings 6+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Don't disclose and Other. Education includes Bachelor of Business Administration, University (Kenya) and Diploma, Online Certification. AI-training focus includes data types such as Video and labeling workflows including Action Recognition and Data Collection.

Labeling Experience

Founder & AI Talent Recruiter (Vanta Workforce)

OtherVideoData Collection

Acted as an AI talent recruiter and evaluated candidates against AI trainer and data annotation role requirements. Assessed fit for RLHF, content moderation, and prompt writing criteria to support hiring for AI data work. Focused on matching candidates to structured AI training and annotation expectations based on role requirements. • Evaluated candidate profiles for AI trainer and data annotation job requirements. • Assessed understanding of RLHF and prompt-writing criteria. • Considered alignment with content moderation and quality expectations. • Built a recruitment pipeline to staff AI training and annotation work.

2025 - Present

Egocentric Video Data Collector (Human Motion Data Workers)

Don't discloseVideoAction Recognition

Collected egocentric (first-person POV) human motion video data and produced labeled annotations to support computer vision and activity recognition training. Labeled activities, object interactions, and scene transitions using the dataset specification and ensured timestamped annotations were accurate. Performed quality review by comparing recorded footage against task scripts and flagging sessions that failed data quality thresholds. • Labeled activities and object interactions within DVR footage. • Annotated timestamped footage with scene descriptions and motion metadata. • Reviewed and quality-checked footage for compliance with scripts. • Reported/flagged sessions with inconsistencies or insufficient data quality.

2026 - 2026

Education

Work History