Jade G.

Key Skills

Software

Telus

Lionbridge

Top Subject Matter

AI Optimization and Prompt Engineering

Online Data Evaluation for AI Input

Text Data Quality and Validation

Top Data Types

Document

Text

Computer Code Programming

Top Task Types

Bounding Box

Classification

Prompt + Response Writing (SFT)

Text Summarization

Translation/Localization

Data Collection

Freelancer Overview

Freelancer / Consultant (AI Training Involving Prompt Engineering). Brings 11+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, Telus, Label box and Scale . Education includes Professional Certificate, Google, Coursera (2025) and Certificate, Universia (2025). AI-training focus includes data types such as Text and labeling workflows including Prompt + Response Writing (SFT), Evaluation, and Rating.

Labeling Experience

Freelancer / Consultant (AI Training Involving Prompt Engineering)

TextPrompt Response Writing SFT

Designed and applied prompt engineering techniques to optimize AI-generated output for business clients. Delivered hands-on solutions using AI tools and improved AI performance by testing, modifying, and refining prompts. Enhanced product insights and engagement through careful prompt crafting and evaluation. • Conducted prompt engineering and evaluation for text-based AI models • Supported data labeling processes to boost model accuracy • Advised on safe, pragmatic AI usage and model adoption • Optimized prompts to improve AI-generated results

Designed and applied prompt engineering techniques to optimize AI-generated output for business clients. Delivered hands-on solutions using AI tools and improved AI performance by testing, modifying, and refining prompts. Enhanced product insights and engagement through careful prompt crafting and evaluation. • Conducted prompt engineering and evaluation for text-based AI models • Supported data labeling processes to boost model accuracy • Advised on safe, pragmatic AI usage and model adoption • Optimized prompts to improve AI-generated results

2017 - Present

Web-Based Evaluation Specialist

TelusText

Applied project guidelines to evaluate, validate, and rate web-based data in a global context. Used online sources and analytical methods to assess the accuracy and reliability of results. Ensured up-to-date and relevant information was provided to enhance AI models' data inputs. • Gathered, verified, and rated data from public websites • Used geospatial and cultural knowledge to inform data validation • Conducted quality checks to maintain consistency and data integrity • Supported large language model tuning through evaluation tasks

Applied project guidelines to evaluate, validate, and rate web-based data in a global context. Used online sources and analytical methods to assess the accuracy and reliability of results. Ensured up-to-date and relevant information was provided to enhance AI models' data inputs. • Gathered, verified, and rated data from public websites • Used geospatial and cultural knowledge to inform data validation • Conducted quality checks to maintain consistency and data integrity • Supported large language model tuning through evaluation tasks

2021 - 2023

Data Quality Operator

TextData Collection

Validated, cleaned, and integrated text data to improve quality for AI and business analytics. Ensured timely, accurate reporting through rigorous data handling and correction. Supported management with reliable data validation for critical business decisions. • Cleaned and integrated raw data inputs into structured formats • Detected and resolved inaccuracies in datasets • Enabled more confident reporting by standardizing data • Maintained high standards for data quality assurance

Validated, cleaned, and integrated text data to improve quality for AI and business analytics. Ensured timely, accurate reporting through rigorous data handling and correction. Supported management with reliable data validation for critical business decisions. • Cleaned and integrated raw data inputs into structured formats • Detected and resolved inaccuracies in datasets • Enabled more confident reporting by standardizing data • Maintained high standards for data quality assurance

2022 - 2022

Quality Specialist – Translation Review/QA

Text

Performed detailed translation review with an emphasis on error detection and linguistic accuracy for AI-supported translation tools. Conducted quality assurance checks to ensure consistent results across multilingual datasets. Delivered final, error-free translations according to strict project guidelines. • Led QA processes for translation error-checking • Improved dataset reliability for downstream AI applications • Adhered strictly to quality standards and timelines • Supported automation by delivering high-integrity language data

Performed detailed translation review with an emphasis on error detection and linguistic accuracy for AI-supported translation tools. Conducted quality assurance checks to ensure consistent results across multilingual datasets. Delivered final, error-free translations according to strict project guidelines. • Led QA processes for translation error-checking • Improved dataset reliability for downstream AI applications • Adhered strictly to quality standards and timelines • Supported automation by delivering high-integrity language data

2021 - 2021

Ads Quality Rater

LionbridgeText

Evaluated ad relevance and accuracy on online platforms using set quality guidelines and web tools. Assessed the effectiveness of ad targeting by applying local and national context to ensure optimized exposure. Provided routine feedback to improve advertising data effectiveness and inform future model training. • Rated accuracy and relevance of digital advertisements • Used online interfaces designed for annotation and review • Focused on accurate application of region-specific guidelines • Improved final data quality for advertising model performance

Evaluated ad relevance and accuracy on online platforms using set quality guidelines and web tools. Assessed the effectiveness of ad targeting by applying local and national context to ensure optimized exposure. Provided routine feedback to improve advertising data effectiveness and inform future model training. • Rated accuracy and relevance of digital advertisements • Used online interfaces designed for annotation and review • Focused on accurate application of region-specific guidelines • Improved final data quality for advertising model performance

2019 - 2020

Education

Work History