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Yitbarek User

@yitbarekuser

AI Data Annotation Specialist on AI training projects, contributing to multimodal labeling and RLHF evaluation.

Ethiopia
Message

Across multiple AI training projects, I’ve contributed to more than 35 projects supporting machine learning and generative AI. My work spans image, video, text, 3D, and audio data.

I’ve contributed to senior-track RLHF workflows by comparing and ranking model responses, evaluating chain-of-thought reasoning, and reporting recurring weaknesses to project leads. I’ve also reviewed content against safety rubrics and flagged edge cases for escalation.

On computer vision and autonomous systems tasks, I’ve annotated images and videos with bounding boxes, semantic segmentation, and temporal event tags. I’ve also annotated LiDAR and point-cloud data, creating 3D bounding boxes and validating spatial reasoning.

I produce and review content in English, Amharic, and Oromo, including transcription, translation, and MTPE. I also bring a Biomedical Engineering background and experience with biomedical equipment maintenance.

Experience

Work history, roles, and key accomplishments

MP
Current

AI Data Annotation & Language Specialist

Multiple AI training projects

Jan 2021 - Present (5 years 10 months)

Contributed to over 35 AI training data projects across image, video, text, 3D, and audio modalities. Enhanced RLHF workflows, reviewed content for safety, and maintained high inter-annotator agreement.

Education

Degrees, certifications, and relevant coursework

MI

Microsoft

Gen AI For Beginners, Generative AI

2024 - 2024

Completed the Gen AI For Beginners course by Microsoft and Github in 2024.

MI

Microsoft

AI For Beginners, Artificial Intelligence

2023 - 2023

Completed the AI For Beginners course by Microsoft and Github in 2023.

HU

Hawassa University

Bachelor of Science, Biomedical Engineering

Bachelor of Science in Biomedical Engineering from Hawassa University, completed in 2022.

HO

Home

ML Engineering, Machine Learning Engineering

Self-study in ML Engineering.

Tech stack

Software and tools used professionally

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