Angel Martin

Key Skills

Software

Data Annotation Tech

Label Studio

Remotasks

Scale AI

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Audio

Video

Top Task Types

Audio Recording

Data Collection

Mapping

Object Detection

Freelancer Overview

I have hands-on experience in AI training and data labeling, particularly in projects that involve computer vision and robotics. My background includes mapping cameras with specific reference points to enhance robotic perception, as well as describing images and videos in detail to identify and classify every element within a scene. This work has allowed me to develop strong attention to detail, consistency in annotation, and a clear understanding of how high-quality labeled data directly impacts the performance of machine learning models. Beyond technical execution, I bring problem-solving skills and a strong analytical mindset. My ability to break down complex visual information into structured datasets makes me a valuable contributor to AI projects that rely on precision and reliability. Combined with my academic foundation in economics and operations management, I also bring an understanding of efficiency, scalability, and the broader impact of AI in practical applications.

Labeling Experience

Audio Recording

LabelboxAudioAudio Recording

In this project, I contributed to the development of speech and language AI systems by recording and curating high-quality audio samples. My responsibilities included following strict guidelines to ensure clarity, accuracy, and consistency across all recordings. I worked with diverse prompts and scripts to capture natural speech patterns, accents, and variations that are essential for training robust speech recognition and natural language processing models. The role required attention to detail, adaptability, and precision in following instructions, as even minor variations in quality could impact the effectiveness of the final dataset. By delivering clean and well-structured audio recordings, I supported the creation of training data that enhances AI performance in tasks such as voice assistants, transcription services, and multilingual applications.

In this project, I contributed to the development of speech and language AI systems by recording and curating high-quality audio samples. My responsibilities included following strict guidelines to ensure clarity, accuracy, and consistency across all recordings. I worked with diverse prompts and scripts to capture natural speech patterns, accents, and variations that are essential for training robust speech recognition and natural language processing models. The role required attention to detail, adaptability, and precision in following instructions, as even minor variations in quality could impact the effectiveness of the final dataset. By delivering clean and well-structured audio recordings, I supported the creation of training data that enhances AI performance in tasks such as voice assistants, transcription services, and multilingual applications.

2025

Robotics Data Collection

Scale AI3D SensorRoutingMapping

This project focused on enhancing robotic systems through the collection and structuring of high-quality data. My role involved mapping cameras with specific reference points to create precise datasets that improved robotic perception and navigation. I was responsible for capturing, labeling, and organizing visual data in different environments, ensuring that every object, feature, and interaction within a scene was clearly identified and categorized. The project required a combination of technical accuracy and consistency, as the datasets collected were directly used to train computer vision models. By carefully annotating images and videos, I contributed to improving object recognition, spatial awareness, and decision-making capabilities in robots. This experience reinforced the importance of data precision in AI training and gave me practical skills in structured labeling, quality control, and collaborative workflows in AI-driven robotics.

This project focused on enhancing robotic systems through the collection and structuring of high-quality data. My role involved mapping cameras with specific reference points to create precise datasets that improved robotic perception and navigation. I was responsible for capturing, labeling, and organizing visual data in different environments, ensuring that every object, feature, and interaction within a scene was clearly identified and categorized. The project required a combination of technical accuracy and consistency, as the datasets collected were directly used to train computer vision models. By carefully annotating images and videos, I contributed to improving object recognition, spatial awareness, and decision-making capabilities in robots. This experience reinforced the importance of data precision in AI training and gave me practical skills in structured labeling, quality control, and collaborative workflows in AI-driven robotics.

2025

Specialist Video Description

Scale AIVideoObject Detection

As a Video Description Specialist at Remotasks, I worked on creating detailed and structured annotations for video content to support AI training in computer vision. My role involved carefully analyzing video sequences and providing frame-by-frame descriptions to identify objects, actions, environments, and interactions. This level of detail was essential for building datasets that allow AI models to recognize movement, context, and complex visual patterns. The position demanded high levels of concentration, accuracy, and consistency, as well as the ability to break down dynamic visual information into meaningful, structured data. By producing comprehensive descriptions and ensuring quality control across my tasks, I contributed to the improvement of AI systems in areas such as autonomous navigation, video understanding, and scene recognition.

As a Video Description Specialist at Remotasks, I worked on creating detailed and structured annotations for video content to support AI training in computer vision. My role involved carefully analyzing video sequences and providing frame-by-frame descriptions to identify objects, actions, environments, and interactions. This level of detail was essential for building datasets that allow AI models to recognize movement, context, and complex visual patterns. The position demanded high levels of concentration, accuracy, and consistency, as well as the ability to break down dynamic visual information into meaningful, structured data. By producing comprehensive descriptions and ensuring quality control across my tasks, I contributed to the improvement of AI systems in areas such as autonomous navigation, video understanding, and scene recognition.

2024 - 2025

Education

Work History