Olivia M.

Key Skills

Software

Remotasks

Top Subject Matter

Chatbot response quality and linguistic evaluation for NLP

Linguistic evaluation for support chatbot documentation

LLM annotation for networking queries and documentation

Top Data Types

Text

Top Task Types

Routing

Freelancer Overview

AI Data Annotation Specialist | Remotasks (Freelance). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Remotasks, Internal, and Proprietary Tooling. Education includes Bachelor of Science, University of Baltimore (2021) and Certification, CompTIA (2024). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Routing.

Labeling Experience

Networking Assistant | Datalink Networks Inc.

TextRouting

Managed LLM annotation workflows for technical networking queries and documentation. Focused on producing correctly labeled information that improves model handling of networking-related user requests. Supported reliable outcomes for enterprise troubleshooting use cases. • Coordinated annotation workflow tasks for LLM outputs • Labeled technical networking query/documentation pairs • Ensured annotations aligned with networking context • Supported enterprise client documentation needs

2024 - Present

IT Support Specialist | ScanSource, Inc.

Text

Optimized internal documentation for automated support chatbots using linguistic evaluation. Applied language-focused quality assessments to improve user resolution rates. Supported continuous refinement of chatbot content based on evaluation outcomes. • Used linguistic evaluation to improve chatbot documentation • Assessed language quality and clarity for end users • Supported higher resolution rates via better phrasing • Contributed to ongoing chatbot content improvements

2023 - 2024

AI Data Annotation Specialist | Remotasks (Freelance)

RemotasksText

Evaluated and improved AI-generated chatbot responses to ensure natural conversational tone and technical accuracy. Focused on assessing quality and consistency of model outputs for real-world usability. Performed linguistic quality checks as part of continuous improvement for assistant behavior. • Rated responses for fluency, tone, and correctness • Checked technical accuracy for domain-specific guidance • Validated conversational coherence and user-understandability • Iterated based on evaluation findings

2023 - 2024

Education

Work History