Zahira Rojas

Key Skills

Software

Appen

CVAT

Data Annotation Tech

Lionbridge

OneForma

Internal/Proprietary Tooling

Top Subject Matter

AI Vision & Computer Vision Data Labeling

Text & Language Model (LLM) Evaluation in English & Spanish

Multi-Modal Data Annotation for AI Systems

Top Data Types

Computer Code Programming

Document

Text

Top Label Types

Classification

Evaluation Rating

Prompt Response Writing SFT

Text Summarization

Translation Localization

Freelancer Overview

With extensive experience in AI training and data labeling, I specialize in vision, text, and multi-modal systems. I have a deep understanding of AI data annotation, from computer vision tasks for autonomous vehicles to evaluating and labeling text for large language models in both English and Spanish. My expertise includes precise image and video annotation, as well as evaluating text generation models to ensure they meet quality and accuracy standards. I have worked on projects spanning various industries, contributing to cutting-edge AI systems that drive innovation in self-driving cars, natural language processing, and more. My ability to handle complex data types and my fluency in multiple languages make me a versatile asset for any AI training project.

Labeling Experience

Text Categorization and Evaluation for LLM Training

AppenTextClassificationText Generation

In this project, I was responsible for categorizing and evaluating large datasets of text used for training language models. My tasks included classifying text into predefined categories, evaluating the relevance and accuracy of AI-generated responses, and ensuring that text outputs adhered to quality standards. I worked with diverse content in English and Spanish, performing both manual annotations and quality checks to ensure the training data was of the highest standard. The project aimed to enhance the language model’s performance in real-world applications such as customer service and content generation.

In this project, I was responsible for categorizing and evaluating large datasets of text used for training language models. My tasks included classifying text into predefined categories, evaluating the relevance and accuracy of AI-generated responses, and ensuring that text outputs adhered to quality standards. I worked with diverse content in English and Spanish, performing both manual annotations and quality checks to ensure the training data was of the highest standard. The project aimed to enhance the language model’s performance in real-world applications such as customer service and content generation.

2023 - 2024

Image Annotation for Autonomous Vehicle Computer Vision

AppenImageEvaluation Rating

This project involved annotating images and videos for autonomous vehicle systems, focusing on object detection and segmentation tasks. I labeled various objects such as pedestrians, vehicles, traffic signs, and road conditions, ensuring that each label was accurate and precise. The data was used to train computer vision models to improve the vehicle's ability to recognize and navigate different environments. I worked closely with the quality assurance team to maintain a high level of accuracy, adhering to strict quality standards and project timelines. The project required handling large datasets and performing multiple quality checks for consistency.

This project involved annotating images and videos for autonomous vehicle systems, focusing on object detection and segmentation tasks. I labeled various objects such as pedestrians, vehicles, traffic signs, and road conditions, ensuring that each label was accurate and precise. The data was used to train computer vision models to improve the vehicle's ability to recognize and navigate different environments. I worked closely with the quality assurance team to maintain a high level of accuracy, adhering to strict quality standards and project timelines. The project required handling large datasets and performing multiple quality checks for consistency.

2022 - 2024

Education

Work History