Victoria Rodriguez

Key Skills

Software

Mercor

Scale AI

Appen

Top Subject Matter

No subject matter listed

Top Data Types

Text

Video

Audio

Top Label Types

Bounding Box

Text Generation

RLHF

Fine Tuning

Red Teaming

Classification

Emotion Recognition

Evaluation Rating

Transcription

Text Summarization

Function Calling

Freelancer Overview

I am a detail-oriented AI Data Specialist with over 10 years of experience in data labeling, annotation, and AI training data workflows across domains including computer vision, NLP, and audio processing. My work includes prompt engineering, output auditing, and preference ranking for large language models and multimodal AI systems, ensuring data quality and ethical standards are met. I am skilled in Python, SQL, Excel, Power BI, and annotation platforms, and have a strong background in collaborating with technical teams to improve annotation tools and processes. My experience spans high-accuracy voice annotation, RLHF, rubric development, and research projects such as breast cancer prediction using machine learning. I am passionate about advancing AI through accurate, innovative, and efficient data practices.

Labeling Experience

Mercor Data Annotation Specialist

MercorTextBounding BoxText Generation

Perform daily preference ranking of hundreds of multimodal AI outputs including images, audio and video against prompts to evaluate model performance and alignment. Maintain high accuracy and throughput in large-scale annotation workflows, contributing to reliable training data for model fine-tuning and preference optimization. Design and audit prompts and outputs for clarity, accuracy, and relevance, ensuring data quality meets evolving project requirements.

Perform daily preference ranking of hundreds of multimodal AI outputs including images, audio and video against prompts to evaluate model performance and alignment. Maintain high accuracy and throughput in large-scale annotation workflows, contributing to reliable training data for model fine-tuning and preference optimization. Design and audit prompts and outputs for clarity, accuracy, and relevance, ensuring data quality meets evolving project requirements.

2025

Outlier AI Data Expert

Scale AIVideoBounding BoxClassification

Develop and refine high-quality prompts to train large language models (LLMs), ensuring alignment with task objectives and linguistic accuracy. ▪ Evaluate and audit LLM-generated outputs for factual correctness, coherence, and adherence to guidelines. Delivered high-accuracy voice annotations for thousands of short video clips, achieving a 4.8/5 quality rating by consistently following evolving client guidelines and maintaining clear, noise-free recordings. Partnered with internal teams to provide structured feedback on annotation tools and workflows, recommending usability improvements that reduced errors and boosted labeling efficiency. Review and provide actionable feedback on peer work to maintain consistency and support team-wide quality assurance initiatives.

Develop and refine high-quality prompts to train large language models (LLMs), ensuring alignment with task objectives and linguistic accuracy. ▪ Evaluate and audit LLM-generated outputs for factual correctness, coherence, and adherence to guidelines. Delivered high-accuracy voice annotations for thousands of short video clips, achieving a 4.8/5 quality rating by consistently following evolving client guidelines and maintaining clear, noise-free recordings. Partnered with internal teams to provide structured feedback on annotation tools and workflows, recommending usability improvements that reduced errors and boosted labeling efficiency. Review and provide actionable feedback on peer work to maintain consistency and support team-wide quality assurance initiatives.

2024

AI Data Annotation Expert

AppenAudioClassificationText Summarization

Supported AI model training through Reinforcement Learning from Human Feedback (RLHF), ensuring ethical and accurate model outputs. Evaluated global search engine results for relevance and safety; applied nuanced judgment to ambiguous or edge-case queries, ensuring more accurate, user-centered results. Conducted prompt engineering, quality audits, and rubric development to support scalable AI system evaluation. Collaborated with global research teams to synthesize model performance feedback and refine training workflows Assessed and improved AI-generated audio outputs by flagging pronunciation, grammar, and fluency issues, contributing to more natural-sounding speech models.

Supported AI model training through Reinforcement Learning from Human Feedback (RLHF), ensuring ethical and accurate model outputs. Evaluated global search engine results for relevance and safety; applied nuanced judgment to ambiguous or edge-case queries, ensuring more accurate, user-centered results. Conducted prompt engineering, quality audits, and rubric development to support scalable AI system evaluation. Collaborated with global research teams to synthesize model performance feedback and refine training workflows Assessed and improved AI-generated audio outputs by flagging pronunciation, grammar, and fluency issues, contributing to more natural-sounding speech models.

2017 - 2018

Education

Work History