Lucas Sousa

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Document

Text

Top Task Types

Computer Programming Coding

Evaluation Rating

Prompt Response Writing SFT

Text Generation

Translation Localization

Freelancer Overview

I have over six months of hands-on experience in evaluating language models and generating text in English, Spanish, and Portuguese. I enjoy the creative process of crafting effective prompts and ensuring that data labeling is done with precision. My work has involved various projects where attention to detail is crucial, and I take pride in contributing to the development of high-quality datasets that enhance AI performance. Beyond my language skills, I have a solid grasp of natural language processing (NLP) and machine learning concepts. I also have experience analyzing and evaluating code, which allows me to provide valuable insights into how models perform. I’m passionate about using my skills to make a real impact in AI training and look forward to contributing to innovative projects across different industries.

Labeling Experience

Multilingual Text Annotation for AI Language Models

Scale AITextEntity Ner ClassificationText Generation

This project involved annotating a diverse dataset to train AI language models for multilingual applications. The scope included labeling text data in English, Spanish, and Portuguese, focusing on identifying named entities, classifying sentiments, and generating contextually relevant prompts. The project encompassed approximately 10,000 text samples, with strict quality measures in place, including peer reviews and consistency checks to ensure high accuracy in the annotations.

This project involved annotating a diverse dataset to train AI language models for multilingual applications. The scope included labeling text data in English, Spanish, and Portuguese, focusing on identifying named entities, classifying sentiments, and generating contextually relevant prompts. The project encompassed approximately 10,000 text samples, with strict quality measures in place, including peer reviews and consistency checks to ensure high accuracy in the annotations.

2024

Education

Work History