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Daberechi A.

Daberechi A.

AI Data Annotation Specialist - Technology & Internet

Nigeria flagEnugu, Nigeria
$16.00/hrIntermediateInternal Proprietary Tooling

Key Skills

Software

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

VideoVideo
ImageImage

Top Task Types

SegmentationSegmentation
Action RecognitionAction Recognition
Bounding BoxBounding Box
Object DetectionObject Detection
Question AnsweringQuestion Answering
RLHFRLHF
Fine-tuningFine-tuning
Evaluation/RatingEvaluation/Rating

Freelancer Overview

I am an experienced data annotation and AI research specialist with a strong background in evaluating and refining AI-generated responses across text, image, audio, and video datasets. My work has focused on enhancing the quality, safety, and empathy of AI outputs by applying structured criteria, critical reasoning, and a human-centered approach. I have contributed to projects involving conversational AI, e-commerce workflows, and digital content moderation, ensuring that datasets are precise, well-documented, and aligned with user needs. My skills include multimodal data labeling, emotional tone assessment, content rewriting, fact-checking, and remote collaboration. I am also certified in data analytics and project management, which supports my ability to deliver high-quality results in fast-paced, remote environments.

IntermediateEnglish

Labeling Experience

GUI Interaction Annotation (Human-Computer Interaction Data Annotation)

Internal Proprietary ToolingVideoBounding BoxSegmentation
Contributed to multimodal AI training projects focused on human-computer interaction and desktop automation. Reconstructed real-world computer workflows by executing structured task prompts across multiple applications and operating systems while recording full-screen sessions. Annotated fine-grained GUI interactions including cursor movements, clicks, scrolls, keystrokes, file navigation, window transitions, and UI state changes. Performed trajectory-based annotation (Observation → Thought → Action), ensuring precise documentation of system states and user intent throughout multi-step workflows. Validated task prompts prior to execution to confirm clarity and feasibility, and applied structured formatting standards (including JSON-based action logging) to maintain dataset consistency. Conducted quality assurance reviews to identify ambiguous instructions, inconsistent UI behaviors, and inaccurate model interpretations of interface elements. Maintained strict adherence to annotation

Contributed to multimodal AI training projects focused on human-computer interaction and desktop automation. Reconstructed real-world computer workflows by executing structured task prompts across multiple applications and operating systems while recording full-screen sessions. Annotated fine-grained GUI interactions including cursor movements, clicks, scrolls, keystrokes, file navigation, window transitions, and UI state changes. Performed trajectory-based annotation (Observation → Thought → Action), ensuring precise documentation of system states and user intent throughout multi-step workflows. Validated task prompts prior to execution to confirm clarity and feasibility, and applied structured formatting standards (including JSON-based action logging) to maintain dataset consistency. Conducted quality assurance reviews to identify ambiguous instructions, inconsistent UI behaviors, and inaccurate model interpretations of interface elements. Maintained strict adherence to annotation

2025 - 2025

Video Annotation Specialist

Internal Proprietary ToolingVideoSegmentationAction Recognition
Contributed to computer vision training projects focused on robotics and interactive gaming environments. Performed fine-grained video annotation by segmenting short-form videos into timestamped intervals and labeling robot activities, object interactions, motion patterns, and contextual events. For robotics datasets, annotations supported action recognition and behavior modeling tasks. For gaming datasets, labeled in-game actions, player movements, environmental interactions, and sequential event flows. Applied structured taxonomies and project-specific guidelines to ensure high annotation consistency and precision. Conducted frame-level and sequence-level labeling where required, maintaining alignment with predefined ontology standards. Participated in quality control workflows, including self-review, peer review, and feedback-based revisions to improve dataset accuracy. Maintained strict data confidentiality and productivity standards while handling high-volume annotation

Contributed to computer vision training projects focused on robotics and interactive gaming environments. Performed fine-grained video annotation by segmenting short-form videos into timestamped intervals and labeling robot activities, object interactions, motion patterns, and contextual events. For robotics datasets, annotations supported action recognition and behavior modeling tasks. For gaming datasets, labeled in-game actions, player movements, environmental interactions, and sequential event flows. Applied structured taxonomies and project-specific guidelines to ensure high annotation consistency and precision. Conducted frame-level and sequence-level labeling where required, maintaining alignment with predefined ontology standards. Participated in quality control workflows, including self-review, peer review, and feedback-based revisions to improve dataset accuracy. Maintained strict data confidentiality and productivity standards while handling high-volume annotation

2025 - 2025

Multimodal AI Response Evaluation

Internal Proprietary ToolingImageQuestion AnsweringRLHF
Contributed to multimodal AI evaluation projects involving image-grounded question answering and response comparison. Generated structured prompts based on image sequences and assessed multiple AI-generated responses for accuracy, contextual alignment, visual grounding, reasoning quality, and clarity. Performed pairwise comparative evaluation, ranking responses according to predefined quality criteria. Identified hallucinations, misinterpretations of visual content, and reasoning gaps. When both responses failed to meet standards, authored corrected, high-quality responses aligned with the visual evidence and project guidelines. Applied structured rating frameworks to ensure consistency across datasets and supported reinforcement learning workflows through human preference feedback. Maintained strict adherence to evaluation rubrics, quality thresholds, and confidentiality standards in high-volume review tasks.

Contributed to multimodal AI evaluation projects involving image-grounded question answering and response comparison. Generated structured prompts based on image sequences and assessed multiple AI-generated responses for accuracy, contextual alignment, visual grounding, reasoning quality, and clarity. Performed pairwise comparative evaluation, ranking responses according to predefined quality criteria. Identified hallucinations, misinterpretations of visual content, and reasoning gaps. When both responses failed to meet standards, authored corrected, high-quality responses aligned with the visual evidence and project guidelines. Applied structured rating frameworks to ensure consistency across datasets and supported reinforcement learning workflows through human preference feedback. Maintained strict adherence to evaluation rubrics, quality thresholds, and confidentiality standards in high-volume review tasks.

2024 - 2025

Education

U

University of Nigeria, Nsukka

Bachelor of Science, Economics

Bachelor of Science
2017 - 2022

Work History

T

Turing

AI Data Annotation & Research Specialist

Remote
2024 - 2025
N

Norrenberger

Business Advisory Intern

Abuja
2023 - 2024