Ashley S.

Key Skills

Software

Appen

Top Subject Matter

Life sciences and general knowledge (LLM training)

Enterprise AI training for Fortune 500 clients (multimodal CV + NLP)

Scientific domain annotation (autonomous vehicle and healthcare)

Top Data Types

Text

Image

Top Task Types

Fine-tuning

Classification

Freelancer Overview

Senior AI Training Specialist at xAI. Core strengths include Internal, Proprietary Tooling, and Appen. Education includes Master of Science, University of Texas at Austin (2020) and Bachelor of Science, Texas A&M University (2018). AI-training focus includes data types such as Text and labeling workflows including Fine-tuning, Evaluation, and Rating.

Labeling Experience

Senior AI Training Specialist at xAI

TextFine-tuning

Curated and labeled large-scale text data for AI training to improve response accuracy and relevance. Designed and implemented training protocols to raise annotation consistency and reduce hallucination behavior. Performed audits on large language model behavior to identify and resolve critical edge cases. • Labeled 500,000+ samples monthly for model training • Improved annotation consistency from 82% to 96% • Increased system reliability by 41% via edge-case resolution • Mentored junior trainers and established cross-team quality control frameworks

2023 - Present

AI Training Lead at Scale AI

Text

Managed end-to-end AI training projects delivering millions of annotated data points with high quality scoring. Developed multimodal training methodologies and supporting evaluation approaches to improve performance metrics across computer vision and language tasks. Created and maintained evaluation rubrics to benchmark model iterations and speed up development cycles. • Delivered 2.5M+ annotated data points with 98.7% quality score • Improved performance metrics by 29% on multimodal tasks • Accelerated development cycles by ~3 weeks using evaluation rubrics • Reduced labeling costs by 22% through automation of repetitive steps

2021 - 2023

AI Data Specialist / Trainer at Appen

AppenTextClassification

Contributed to training datasets by labeling data instances for autonomous vehicle and healthcare AI projects. Achieved strong performance ranking based on accuracy, speed, and consistency metrics. Provided domain-informed feedback by identifying and documenting model weaknesses to guide later training. • Processed 150,000+ data instances per quarter • Ranked in the top 5% of 400+ trainers on quality metrics • Performed scientific domain annotation to ensure technical accuracy • Supplied actionable feedback on systemic model weaknesses

2019 - 2020

Education