Marilyn Cabrera-sanchez

Key Skills

Software

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Video

Top Label Types

Bounding Box

Entity Ner Classification

Object Detection

Prompt Response Writing SFT

Segmentation

Classification

Evaluation Rating

Text Generation

Translation Localization

Audio Recording

Transcription

Freelancer Overview

I am an experienced data annotator with a background in psychological science and hands-on expertise in labeling and evaluating short video content for AI training. My role at Telus Digital involved following detailed annotation guidelines, maintaining high accuracy, and ensuring data quality by flagging ambiguous content. I am skilled in data analysis using Microsoft Excel and SPSS, and have managed sensitive data in both healthcare and administrative environments. My experience spans computer vision tasks, medical data entry, and academic research, allowing me to bring strong attention to detail, critical thinking, and a commitment to data integrity to every project. I am proficient in both English and Spanish, and thrive in fast-paced, independent work settings.

Labeling Experience

Project Sonic

TelusAudioText GenerationTranslation Localization

Project Sonic involved comprehensive audio data annotation and linguistic labeling to support the training and evaluation of AI and machine learning models. The scope of work included audio transcription, text generation review, translation validation, and speech content classification, following detailed project-specific guidelines. Contributors ensured high levels of accuracy, contextual understanding, and consistency across diverse audio datasets. Project quality was measured through regular audits, peer review processes, and strict adherence to TELUS Digital’s performance, accuracy, and data confidentiality standards.

Project Sonic involved comprehensive audio data annotation and linguistic labeling to support the training and evaluation of AI and machine learning models. The scope of work included audio transcription, text generation review, translation validation, and speech content classification, following detailed project-specific guidelines. Contributors ensured high levels of accuracy, contextual understanding, and consistency across diverse audio datasets. Project quality was measured through regular audits, peer review processes, and strict adherence to TELUS Digital’s performance, accuracy, and data confidentiality standards.

2025 - 2025

Project Sonic

TelusVideoEntity Ner ClassificationSegmentation

Project Sonic involved large-scale video data annotation and content generation to support AI and machine learning model training. Responsibilities included entity classification, segmentation, as well as writing and evaluating prompt–response pairs based on visual scenarios. Work required accurate interpretation of motion, context, and sequencing across frames while adhering to detailed annotation guidelines. Quality was measured through audits, peer review, and strict compliance with TELUS Digital’s accuracy, consistency, and data confidentiality standards.

Project Sonic involved large-scale video data annotation and content generation to support AI and machine learning model training. Responsibilities included entity classification, segmentation, as well as writing and evaluating prompt–response pairs based on visual scenarios. Work required accurate interpretation of motion, context, and sequencing across frames while adhering to detailed annotation guidelines. Quality was measured through audits, peer review, and strict compliance with TELUS Digital’s accuracy, consistency, and data confidentiality standards.

2025 - 2025

Project Sonic

TelusImageBounding BoxEntity Ner Classification

Project Sonic involved large-scale image data annotation to support computer vision and AI model development. Tasks included entity classification, object identification, bounding box annotation, and image attribute labeling, performed in accordance with detailed project guidelines. Work required strong visual analysis, consistency across high-volume datasets, and precise application of labeling standards. Quality was evaluated through ongoing audits, peer reviews, and strict adherence to TELUS Digital’s accuracy, performance, and data confidentiality requirements.

Project Sonic involved large-scale image data annotation to support computer vision and AI model development. Tasks included entity classification, object identification, bounding box annotation, and image attribute labeling, performed in accordance with detailed project guidelines. Work required strong visual analysis, consistency across high-volume datasets, and precise application of labeling standards. Quality was evaluated through ongoing audits, peer reviews, and strict adherence to TELUS Digital’s accuracy, performance, and data confidentiality requirements.

2025 - 2025

Education

Work History