Joshua S.

Key Skills

Software

Scale AI

Appen

Lionbridge

Top Subject Matter

Large Language Models (LLMs)

Natural Language Processing

AI Safety

Top Data Types

Text

Document

Top Task Types

Classification

Freelancer Overview

AI Trainer. Core strengths include Scale AI, Appen, and Lionbridge. Education includes Bachelor of Science, University of Texas (2020). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

AI Trainer

Scale AIText

As an AI Trainer at Scale AI, I am responsible for training and evaluating large language models. My work enhances model accuracy, coherence, and user safety across generative tasks. I frequently develop prompts and conduct quality assurance to improve output relevance and compliance. • Train and evaluate LLMs for improved performance. • Develop and refine AI prompts and responses. • Conduct quality assurance and safety reviews. • Collaborate with engineering on feedback and continual model improvement.

2023 - Present

Data Annotator

AppenTextClassification

In my role at Appen, I performed annotation and categorization on datasets for AI training. My responsibilities included reviewing AI-generated outputs for bias and policy compliance. Additionally, I contributed to the training of NLP and content moderation models. • Annotated and classified text datasets. • Reviewed and rated AI outputs for accuracy and fairness. • Participated in high-volume, supervised ML projects. • Maintained high accuracy standards on all assignments.

2022 - 2023

Data Labeling Specialist

LionbridgeTextClassification

At Lionbridge, I conducted large-scale data labeling and validation projects for AI applications. My work included training multilingual AI models across various domains. I consistently delivered results under tight deadlines and evolving guidelines. • Performed text data labeling for AI system training. • Validated and ensured quality of labeled datasets. • Assisted in multilingual and cross-domain model development. • Demonstrated reliability and on-time task delivery.

2021 - 2022

Education