Raphael N.

Key Skills

Software

Micro1

Don't disclose

Clickworker

iMerit

Labelbox

Label Studio

Mindrift

Toloka

Telus

CVAT

Top Subject Matter

Computer vision video understanding

Annotation workflow operations and guideline enforcement

General ML dataset annotation

Top Data Types

Video

Image

Text

Top Task Types

Action Recognition

Fine-tuning

Classification

Question Answering

Bounding Box

Segmentation

Entity (NER) Classification

Object Detection

Transcription

Polygon

Data Collection

Freelancer Overview

I have experience working on AI training data and data labeling projects involving image annotation, video annotation, captioning, content evaluation, and quality assurance for machine learning models. My work focuses on creating accurate, detailed, and guideline-compliant annotations while maintaining consistency and high quality across datasets. What sets me apart is my strong attention to detail, analytical thinking, and ability to quickly adapt to complex project guidelines and tools. I consistently deliver precise, reliable work, communicate effectively in remote teams, and understand the importance of high-quality data in improving AI model performance.

Labeling Experience

Operational SME (Hugo Technologies)

Don't discloseVideoFine-tuning

As an Operational Subject Matter Expert, you supported onboarding and ongoing training for new annotators. You coached annotators with feedback and retraining to improve annotation performance and consistency at scale. You interpreted complex annotation guidelines and translated them into clear, actionable instructions that met quality and policy standards. • Acted as the primary subject matter expert for data annotation workflows. • Ensured annotations met quality, accuracy, and policy requirements. • Produced examples and best-practice references for training materials. • Coordinated with annotation teams to enforce guideline adherence.

2025 - Present

Data Annotators (Freelance) (e2f, inc.)

Don't discloseTextQuestion Answering

You annotated large datasets for a Response Correctness project, ensuring high accuracy and quality. You evaluated responses for correctness and provided detailed annotations and feedback to guide improvement. You utilized data annotation tools to label data efficiently and accurately for quality-focused dataset creation. • Checked response correctness against expected criteria. • Added detailed feedback to support dataset and model refinement. • Applied annotation tooling for consistent labeling. • Maintained accuracy and quality across large-scale tasks.

2024 - Present

Data Annotators (Freelance) (Moonvalley)

Don't discloseTextClassification

As a freelance data annotator, you annotated extensive datasets for machine learning models with a focus on achieving high accuracy and quality. You used data annotation tools to label data effectively and precisely. You also performed quality control checks to ensure the annotations maintained the required accuracy and overall quality. • Produced ML-ready labeled outputs for downstream model training. • Applied tooling to support consistent, precise annotation work. • Conducted QA/QC checks to detect and correct labeling issues. • Ensured annotation quality aligned with project expectations.

2024 - Present

ML Data Labeler (micro1)

Micro1VideoSegmentation

You annotated video data by labeling objects, actions, scenes, and events according to detailed project guidelines. You created timestamped annotations including scene boundaries, character actions, interactions, and environmental details. You reviewed and corrected annotations based on QA feedback while updating guideline understanding over time. • Maintained attention to lighting conditions, camera angles, motion, and scene transitions. • Ensured annotations were consistent with the latest project instructions. • Performed iterative correction cycles driven by QA evaluation. • Delivered ML-ready, time-aligned video labels for downstream training.

2025 - 2025

Quality Analyst (Hugo Technologies)

Don't discloseImage

You served as a Quality Analyst by regularly reviewing and evaluating samples of annotated data produced by agents. You assessed accuracy, consistency, and adherence to labeling guidelines across production batches. You provided constructive feedback to agents and collaborated with project management to address quality concerns and implement corrective actions. • Evaluated labeled samples for guideline compliance and accuracy. • Delivered feedback highlighting improvement areas and best practices. • Worked cross-functionally to resolve quality issues. • Supported corrective action implementation after QA findings.

2024 - 2025

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Education

Work History