Theo Montanes

Key Skills

Software

Data Annotation Tech

Top Subject Matter

Large Language Models

Natural Language Processing

Finance

Top Data Types

Text

Image

Top Task Types

Classification

Freelancer Overview

AI Trainer – Outlier AI. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Outlier AI and Data Annotation Tech. Education includes Master of Science in Management, ESSEC Business School (2024) and Academic Exchange Program, Keio University (2026). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Data Annotator – DataAnnotation.tech

Data Annotation TechTextClassification

I annotated and categorized text datasets following multiple labeling schemas for NLP model training. I performed transcription of audio content in both French and English with a focus on high accuracy. Additionally, I participated in peer review of annotations to ensure consistency and quality. • Labeled text data for NLP applications • Transcribed audio for speech and language models • Reviewed and flagged annotation inconsistencies • Adapted quickly to different annotation guidelines

I annotated and categorized text datasets following multiple labeling schemas for NLP model training. I performed transcription of audio content in both French and English with a focus on high accuracy. Additionally, I participated in peer review of annotations to ensure consistency and quality. • Labeled text data for NLP applications • Transcribed audio for speech and language models • Reviewed and flagged annotation inconsistencies • Adapted quickly to different annotation guidelines

2025 - Present

AI Trainer – Outlier AI

Text

I evaluated and ranked LLM-generated responses in both French and English for RLHF training pipelines. My work included judging outputs on factual accuracy, instruction-following, tone, coherence, and safety using detailed rubrics. I maintained high accuracy and provided written rationales to improve model alignment. • Evaluated LLM outputs for quality and safety • Ranked and scored diverse prompt responses • Used annotation schemas tailored to project needs • Contributed to RLHF by providing preference labels

I evaluated and ranked LLM-generated responses in both French and English for RLHF training pipelines. My work included judging outputs on factual accuracy, instruction-following, tone, coherence, and safety using detailed rubrics. I maintained high accuracy and provided written rationales to improve model alignment. • Evaluated LLM outputs for quality and safety • Ranked and scored diverse prompt responses • Used annotation schemas tailored to project needs • Contributed to RLHF by providing preference labels

2025 - Present

Education

Work History