Sarae Jonsonson

Key Skills

Software

Appen

Clickworker

CloudFactory

CVAT

Dataloop

Google Cloud Vertex AI

Labelbox

OneForma

Remotasks

Scale AI

Telus

Top Subject Matter

Technical Writing & Documentation:

LLM evaluation in German

Data Annotation

Top Data Types

Computer Code Programming

Image

Video

Top Task Types

Bounding Box

Classification

Computer Programming Coding

Text Generation

Translation Localization

Freelancer Overview

As an experienced data labeling specialist, I have honed my skills in annotating diverse datasets for AI and machine learning applications, particularly in natural language processing (NLP), computer vision, and healthcare domains. My expertise lies in accurately labeling text, images, and video data to ensure the highest quality training data for AI models. With a deep under or AI models. With a deep understanding of AI principles, I effectively collaborate with data scientists and engineers to align labeling efforts with project goals, consistently delivering data that enhances model performance. Throughout my career, I have successfully managed and executed data labeling projects, contributing to high-impact AI models in various industries. My proficiency with labeling tools such as Labelbox and Amazon SageMaker Ground Truth, combined with my commitment to quality assurance, ensures that the data I provide is both reliable and precise. My attention to detail, strong communication skills, and ability to quickly adapt to new guidelines make me a valuable asset in any AI training data team.

Labeling Experience

Object Detection for Autonomous Vehicles

Scale AIVideoCuboid

Project Description: In a project aimed at enhancing autonomous vehicle technology, I labeled thousands of images to identify and classify objects such as pedestrians, vehicles, and road signs. The data was crucial for training a computer vision model to detect and react to objects in real-time. Impact: The resulting model improved the safety and reliability of autonomous driving systems, supporting the development of next-generation self-driving cars.

Project Description: In a project aimed at enhancing autonomous vehicle technology, I labeled thousands of images to identify and classify objects such as pedestrians, vehicles, and road signs. The data was crucial for training a computer vision model to detect and react to objects in real-time. Impact: The resulting model improved the safety and reliability of autonomous driving systems, supporting the development of next-generation self-driving cars.

2021 - 2023

Data Labeling/AI Training Experience

Scale AIImageBounding Box

Project Description: I worked on a large-scale sentiment analysis project, labeling over 50,000 customer reviews to train a model for detecting positive, negative, and neutral sentiments. My role involved meticulously annotating text data and ensuring consistency across annotations by following detailed guidelines. Impact: The project significantly improved the accuracy of the sentiment analysis model, which was later implemented to enhance customer feedback systems for a major e-commerce platform.

Project Description: I worked on a large-scale sentiment analysis project, labeling over 50,000 customer reviews to train a model for detecting positive, negative, and neutral sentiments. My role involved meticulously annotating text data and ensuring consistency across annotations by following detailed guidelines. Impact: The project significantly improved the accuracy of the sentiment analysis model, which was later implemented to enhance customer feedback systems for a major e-commerce platform.

2021 - 2023

Entity Recognition for Financial Document Processing

CloudfactoryTextText Generation

Project Description: I participated in an NLP project focused on extracting key information from financial documents, such as invoices and contracts. My task was to label entities like dates, amounts, and company names, which were then used to train an entity recognition model. Impact: The model streamlined document processing for a financial services company, reducing manual data entry and increasing operational efficiency.

Project Description: I participated in an NLP project focused on extracting key information from financial documents, such as invoices and contracts. My task was to label entities like dates, amounts, and company names, which were then used to train an entity recognition model. Impact: The model streamlined document processing for a financial services company, reducing manual data entry and increasing operational efficiency.

2018 - 2020

Education

Work History