Caitlin C.

Key Skills

Software

Other

Don't disclose

Top Subject Matter

LLM output evaluation

dataset QA

and safety policy review

Top Data Types

Text

Top Task Types

Evaluation/Rating

RLHF

Text Generation

Question Answering

Text Summarization

Red Teaming

Freelancer Overview

AI Data Annotation Specialist (DataAnnotation). Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other and Don't disclose. Education includes Certificate, St. Petersburg College (2021) and Bachelor of Arts, University of South Florida (2014). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI Data Annotation Specialist (DataAnnotation)

OtherText

Evaluated LLM outputs using structured rubrics to assess accuracy, clarity, reasoning quality, and safety, then generated feedback to guide improvements. Labeled and QA’d large training datasets across multiple domains, focusing on identifying edge cases and inconsistencies that impact dataset quality. Performed safety reviews that included policy adherence checks, harmful-content detection, and documented failure modes for model retraining cycles. • Assessed outputs against rubric dimensions (accuracy, clarity, reasoning, safety). • Detected edge cases, systematic failure patterns, and data inconsistencies. • Documented safety-related failure modes for iterative retraining. • Provided evaluation feedback to improve model alignment and dataset integrity.

2025 - Present

Software Engineer in Test (QA Analyst) at Catalis Tax & CAMA

Don't discloseText

Conducted structured QA validation for backend and UI releases, with emphasis on verifying data accuracy and business rules across complex workflows. Wrote and executed SQL-based checks to validate backend data integrity, reconcile calculations, and identify defects in large-scale datasets. Supported SDLC regression testing and production-readiness verification to ensure reliable system behavior before release. • Verified functionality, business rules, and data accuracy across workflows. • Used complex SQL queries to detect data integrity issues and defects. • Reproduced and documented defects with backend engineers using SQL steps. • Performed regression testing and confirmed production readiness per release.

2022 - 2025

Education

Work History