Alfonso G.

Key Skills

Software

Scale AI

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Freelancer Overview

I am an experienced data scientist and AI engineer with a strong background in data labeling, annotation, and AI training data workflows. My expertise includes designing and evaluating datasets for large language models (LLMs), prompt engineering, and benchmarking AI outputs for accuracy and fairness. I have worked on high-impact projects involving NLP, code reasoning, and multimodal data (text, image, code), and have developed validation frameworks and annotation tools to improve model training and evaluation. My technical skills span Python, SQL, TensorFlow, PyTorch, and cloud-native tools, and I am comfortable collaborating with remote, cross-functional teams to ensure high-quality, scalable data pipelines and annotation processes. Notable projects include PromptScorer and LLM Prompt Tracker Dashboard, which demonstrate my commitment to advancing structured evaluation and iterative improvement of AI systems.

Labeling Experience

AI Training Data Labeling Specialist

Scale AITextEvaluation Rating

Worked on large-scale AI training datasets, focusing on data labeling and annotation for machine learning models. Tasks included: Data Cleaning & Validation – Ensured text-based datasets were free of errors, inconsistencies, and duplicates before annotation. Entity Recognition & Classification – Labeled text data with relevant categories for AI model training. Text Summarization & Fine-Tuning – Assisted in training NLP models by summarizing and refining datasets for better performance. Evaluation & Rating – Assessed AI-generated outputs for accuracy and alignment with expected results. Process Optimization – Developed streamlined workflows for labeling, improving project efficiency by 20%.

Worked on large-scale AI training datasets, focusing on data labeling and annotation for machine learning models. Tasks included: Data Cleaning & Validation – Ensured text-based datasets were free of errors, inconsistencies, and duplicates before annotation. Entity Recognition & Classification – Labeled text data with relevant categories for AI model training. Text Summarization & Fine-Tuning – Assisted in training NLP models by summarizing and refining datasets for better performance. Evaluation & Rating – Assessed AI-generated outputs for accuracy and alignment with expected results. Process Optimization – Developed streamlined workflows for labeling, improving project efficiency by 20%.

2020 - 2023

Education

Work History