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Fernando Sanchez

AI & Data Quality Specialist (Independent)

MEXICO flag
Mexico, Mexico
$25.00/hrExpertLabel StudioArgillaLabelbox

Key Skills

Software

Label StudioLabel Studio
ArgillaArgilla
LabelboxLabelbox
DoccanoDoccano

Top Subject Matter

Spanish Language NLP & LLM Evaluation
Software Development & Code Review
Finance & Risk Analysis

Top Data Types

TextText
ImageImage
VideoVideo

Top Task Types

RLHF
Evaluation Rating
Red Teaming
Text Generation
Classification
Prompt Response Writing SFT

Freelancer Overview

Bilingual (Spanish/English) AI Data Quality Specialist with 11+ years in software engineering and 1+ year focused on AI training data. Native Mexican Spanish speaker with deep technical expertise in evaluating LLM outputs for accuracy, fluency, cultural relevance, and safety. Experienced in RLHF workflows, red-teaming, factual verification, and annotation guideline development. Strong background in NLP, data pipelines, and quality assurance across complex systems (AWS, PostgreSQL, Python, Go). Unique combination of native linguistic expertise and senior-level technical understanding — able to evaluate both natural language and code-related AI outputs with precision.

ExpertEnglishSpanish

Labeling Experience

AI & Data Quality Specialist (Independent)

TextRLHF
Evaluated and ranked thousands of AI-generated responses in Mexican Spanish across multiple LLM platforms. Tasks included RLHF preference ranking, factual accuracy verification, cultural adaptation review, and red-teaming exercises. Developed annotation rubrics for Spanish-language NLP tasks including sentiment analysis, entity recognition, and text classification. Focused on identifying edge cases, biases, and failure modes specific to Latin American Spanish. Delivered consistent 95%+ inter-annotator agreement scores on quality metrics.

Evaluated and ranked thousands of AI-generated responses in Mexican Spanish across multiple LLM platforms. Tasks included RLHF preference ranking, factual accuracy verification, cultural adaptation review, and red-teaming exercises. Developed annotation rubrics for Spanish-language NLP tasks including sentiment analysis, entity recognition, and text classification. Focused on identifying edge cases, biases, and failure modes specific to Latin American Spanish. Delivered consistent 95%+ inter-annotator agreement scores on quality metrics.

2024 - Present

Education

U

UNITEC Campus Atizapan

Bachelor of Science, Computer Systems Engineering

Bachelor of Science
2012 - 2017

Work History

T

Th3Code

Full Stack Developer

Mexico City
2022 - 2024
E

Espora Estudio

Full Stack Developer

Mexico City
2020 - 2021