Michael U.

Key Skills

Software

AWS SageMaker

Appen

Clickworker

CloudFactory

CrowdFlower

Data Annotation Tech

Deep Systems

Top Subject Matter

E-commerce - Product categorization & Customer Support

Healthcare - Medical Records & Field Data Expertise

Finance - Risk Analysis & Fraud Detention

Top Data Types

Text

Video

Image

Top Task Types

Text Summarization

Evaluation/Rating

Data Collection

Text Generation

Freelancer Overview

I have hands-on experience in data labeling, annotation, and AI training workflows, with a strong focus on accuracy, consistency, and adherence to detailed guidelines. My work spans text classification, sentiment analysis, content moderation, intent detection, and conversational AI evaluation, where I’ve developed a sharp eye for linguistic nuance and contextual interpretation. I’m skilled at following complex instructions, identifying edge cases, and providing high‑quality labels that improve model performance. What sets me apart is my ability to combine analytical thinking with clear communication, ensuring that every annotation reflects both precision and intent. I’m comfortable working with structured and unstructured data, adapting quickly to new labeling tools, and maintaining high throughput without sacrificing quality. I approach AI training with a problem‑solver mindset—always looking for patterns, inconsistencies, and opportunities to refine datasets so models learn more effectively.

Labeling Experience

ElevenLabs

TextEvaluation/Rating

In this project, I applied my agronomy background to support the development of AI systems designed to understand agricultural data, field reports, and environmental observations. My role involved labeling and classifying text‑based agronomic information, including crop health descriptions, soil condition notes, pest and disease indicators, and environmental factors affecting yield. I annotated datasets for entity recognition, classification, sentiment/context interpretation, and decision‑based labeling, ensuring that the model could accurately interpret real‑world agricultural scenarios.

2024 - 2025

Education

Work History