Pablo Alvarez- García

Key Skills

Software

Remotasks

Scale AI

Toloka

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Document

Text

Top Task Types

Computer Programming Coding

Evaluation Rating

Fine Tuning

Prompt Response Writing SFT

Question Answering

Freelancer Overview

As a bilingual AI training data specialist with hands-on experience in LLM prompt evaluation, I have contributed to projects focused on improving AI assistant performance through structured scoring, multi-turn dialogue analysis, and error tagging. At Outlier, I work on evaluating complex user-assistant interactions in both English and Spanish, identifying issues like hallucinations, tone mismatches, incomplete reasoning, and tool misuse. My role also includes crafting high-quality feedback and critic comments that guide model improvements and enhance natural language alignment. With a strong foundation in education, ICT, and natural language understanding, I bring a unique perspective to annotation and model assessment. My academic training in AI and prompt engineering, combined with experience in curriculum design and user-focused communication, allows me to consistently deliver high-quality, human-like evaluations that help shape the next generation of AI systems.

Labeling Experience

LLM Prompt Evaluation and Multi-turn AI Assistant Training

Scale AITextText GenerationText Summarization

Worked on improving large language model (LLM) performance through structured prompt-response evaluations. Responsibilities included reviewing multi-turn assistant dialogues in English and Spanish, scoring based on clarity, helpfulness, tone, and factual accuracy, and tagging issues like hallucinations, incomplete reasoning, tool misuse, or user intent mismatch. Produced high-quality feedback and critic comments to guide model improvements. Evaluated prompts across various domains, including productivity, education, and general user queries. Maintained high-quality ratings across thousands of evaluations while meeting rigorous deadlines and task quotas.

Worked on improving large language model (LLM) performance through structured prompt-response evaluations. Responsibilities included reviewing multi-turn assistant dialogues in English and Spanish, scoring based on clarity, helpfulness, tone, and factual accuracy, and tagging issues like hallucinations, incomplete reasoning, tool misuse, or user intent mismatch. Produced high-quality feedback and critic comments to guide model improvements. Evaluated prompts across various domains, including productivity, education, and general user queries. Maintained high-quality ratings across thousands of evaluations while meeting rigorous deadlines and task quotas.

2025

Education

Work History