Leo R.

Key Skills

Software

Remotasks

Top Subject Matter

Conversational AI evaluation and prompt quality

Machine learning conversational AI dataset annotation

Backend/API support for AI-adjacent workflows

Top Data Types

Text

Top Task Types

Classification

Data Collection

Evaluation/Rating

Prompt + Response Writing (SFT)

RLHF

Transcription

Freelancer Overview

Software Engineer & AI Operations Specialist (AI evaluation and annotation review). Brings 13+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Remotasks. Education includes Master of Science, University of Central Florida (2015) and Bachelor of Science, Florida State University (2012). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Software Engineer & AI Operations Specialist (AI evaluation and annotation review)

Text

Conducted AI response evaluations, prompt testing, and annotation reviews to improve conversational AI accuracy and consistency. Reviewed AI outputs for quality and reliability while supporting structured testing and validation processes across AI-related workflows. Collaborated with engineering and operations teams to identify issues and improve platform performance. • Performed prompt evaluation and AI response grading • Checked annotations for consistency and quality • Implemented structured QA review and validation steps • Provided feedback loops to reduce revision cycles and improve turnaround time

2021 - Present

Generalist AI Trainer & Annotator

RemotasksTextClassification

Evaluated and labeled large-scale datasets used for machine learning and conversational AI model training. Reviewed AI-generated content for quality, relevance, factual consistency, and instruction adherence. Maintained high annotation accuracy while working on text classification, search relevance, and language evaluation tasks. • Labeled and scored dataset examples for training • Assessed factual consistency and instruction adherence • Identified output inconsistencies and provided structured feedback • Supported language evaluation and search relevance labeling projects

2022 - 2023

Software Engineer Intern

TextData Collection

Supported software development activities including debugging and API testing in an agile environment. While the role was primarily engineering-focused, it included participation in code reviews and maintaining application improvements that supported data and backend operations used by AI-adjacent workflows. No explicit standalone data labeling or AI training tasks are described in the resume for this internship. • Assisted with frontend/backend development and troubleshooting • Supported API testing and database updates • Participated in code reviews in agile cycles • Contributed to internal software improvement delivery

2014 - 2014

Education

Work History