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My Airdrop

@myairdrop

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I label and validate image, audio, and video data to improve AI training pipelines.

Nigeria

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What I'm looking for

I'm looking for remote AI data annotation work where I can label and validate image, audio, and video data, perform quality reviews, and support accurate model training pipelines.

I've supported AI data projects remotely at Appen, Crowdgen, and Atlas, labeling and reviewing image, audio, video, PDFs, and audiobooks.

At Crowdgen and Atlas, I analyzed visual and audio content in video clips against AI-generated written outputs, making corrections where needed. I focus on reconciling AI outputs with available data and improving label consistency through quality reviews.

I hold a BSc in Computer Science and have over two years of hands-on annotation experience. I also led a five-person university team training AI to debug a crashed website.

Experience

Work history, roles, and key accomplishments

Data Annotation

Atlas

Dec 2025 - Aug 2026 (8 months)

Analyzed video clips against AI-written outputs and made corrections where necessary to improve accuracy.

Data Annotation video analysis Quality Assurance Corrections

AI Annotator

Crowdgen

Oct 2024 - Jan 2026 (1 year 3 months)

Analyzed visual and audio content in video clips to verify alignment with AI-generated written outputs.

Data Annotation video analysis Audio Analysis Quality Assurance

AI Labeller

Appen

Nov 2023 - Aug 2024 (9 months)

Identified and labeled required data from provided PDF files, images, and audiobooks to support AI model training.

Data Labeling Data Annotation PDF Processing Image Annotation Audio Annotation

Education

Degrees, certifications, and relevant coursework

Ambrose Alli University

Bachelor of Science, Computer Science

2019 - 2024

Activities and societies: Team leader of a group of five people that trained artificial intelligence to debug a crash website with 17min 52sec.

BSc in Computer Science from Ambrose Alli University, Ekpoma. Led a team of five that trained artificial intelligence to debug a crash website in 17 minutes 52 seconds.