Victor A.

Key Skills

Software

Other

CVAT

Label Studio

Micro1

Top Subject Matter

Video annotation QA and multimodal evaluation (action/video/caption alignment) for real-world and robotics task videos

Video caption QA and caption editing for video understanding

First-person/task video labeling of actions and hand-object interactions (dense/temporal annotation)

Top Data Types

Video

Audio

Image

Text

Document

Top Task Types

Bounding Box

Classification

RLHF

Segmentation

Entity (NER) Classification

Polygon

Object Detection

Question Answering

Transcription

Prompt + Response Writing (SFT)

Data Collection

Text Generation

Action Recognition

Freelancer Overview

Video Data Reviewer at Micro1 (Remote). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Micro1, Other, and N. Education includes Bachelor of Science, University of Ilorin (2022). AI-training focus includes data types such as Video and Audio and labeling workflows including Evaluation, Rating, and Text Generation.

Labeling Experience

Video Data Reviewer at Micro1 (Remote)

Micro1Video

Reviewed AI-generated video annotations for action accuracy, timestamp precision, caption-to-video alignment, and hand-object interaction quality. Used detailed rubrics and evaluation guidelines to detect hallucinations, omissions, unsupported actions, incorrect object descriptions, and ambiguous labels. Supplied concise, structured feedback and applied guideline-based corrections while preserving valid annotations. • Action accuracy and label validity checks • Timestamp precision and temporal consistency validation • Caption-to-video alignment verification • Error detection (hallucinations/omissions) with rubric evidence

2026 - Present

Data Labelling Trainee

OtherVideoClassificationData Collection

Performed dense labeling of first-person and task-based videos by identifying meaningful hand-object interactions, activity sequences, and fine-grained actions. Segmented recordings into temporal windows to separate physical tasks, micro-actions, and atomic actions for structured annotation workflows. Validated submissions for clarity, camera perspective, recording quality, protocol adherence, and accurate attribute-based object naming. • Fine-grained hand-object interaction labeling • Temporal windowing into tasks/micro-actions/atomic actions • Timestamp refinement and annotation synchronization • Submission QA including perspective and protocol checks

2026 - Present

Computer Vision Annotation Trainee

CVATImageBounding Box

As a Computer Vision Annotation Trainee at CVAT.ai Academy, I specialized in reviewing and labeling visual data using CVAT workflows. My tasks included object identification, bounding box annotation, and visual QA for image-based datasets. I ensured accuracy, consistency, and compliance with annotation project guidelines. • Performed object detection and bounding box labeling using CVAT • Reviewed images for label consistency and edge-case handling • Adhered to project annotation guidelines and best practices • Carried out visual quality assurance prior to submission

2026 - Present

Nursing Student / Clinical and Academic Training | University of Ilorin | Nigeria | Year 4 | 2022-Present

Classification

Pursuing clinical and academic training in a healthcare domain with an emphasis on confidentiality, ethical judgment, and structured documentation habits. Built medical terminology knowledge and discipline that supports healthcare and sensitive-data annotation work. Prepared to contribute to patient-safety and ethics-aware labeling projects involving medical content. • Developed medical terminology and structured documentation skills relevant to medical content labeling • Strengthened confidentiality and ethical judgment for handling sensitive healthcare data • Built patient-safety awareness and bias/safety sensitivity for annotation tasks • Prepared for healthcare/wellness and sensitive-data annotation use cases

2022 - Present

Video Caption Specialist at Micro1 (Remote)

Micro1VideoText Generation

Assessed AI-generated video captions for alignment with visible actions, object use, event sequence, and final task outcomes. Edited captions for clarity, grammar, concision, and precise action wording without adding unsupported assumptions. Flagged overstatements and inaccurate descriptions when the video evidence supported narrower interpretations. • Caption-to-video alignment review • Caption rewriting for clarity and concision • Detection of overstatements/inaccuracies • Ensuring event sequence matches visible actions

2026 - 2026

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Education

Work History