Monica Esteban

Key Skills

Software

Appen

Lionbridge

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Prompt Response Writing SFT

Text Summarization

Translation Localization

Freelancer Overview

I worked for approximately 9 months with Appen and Lionbridge on search engine evaluation projects involving text, image, and video content. My tasks focused on assessing user intent, relevance, and quality of search results across different modalities. While these projects didn’t involve AI directly, they followed structured annotation and evaluation frameworks, which align closely with AI training workflows. In addition, I bring experience in UX, content strategy, and product workflows, which strengthens my ability to evaluate outputs critically and consistently. I’m fluent in both Spanish and English, highly adaptable, and comfortable working with detailed guidelines and ambiguity—key skills for training high-quality AI systems.

Labeling Experience

Arrow

AppenTextClassification

I worked on the Arrow project at Appen, which involved evaluating search engine results. For each query, I was presented with different result options (text, image, or video) and had to assess their relevance, usefulness, and alignment with the user’s intent. My role included classifying each result according to strict guidelines and providing detailed feedback to explain my ratings. This work required careful analysis of linguistic nuance, content quality, and context, as well as consistency across evaluations. While not labeled as AI at the time, this process directly supports training and improving search algorithms and large language models.

I worked on the Arrow project at Appen, which involved evaluating search engine results. For each query, I was presented with different result options (text, image, or video) and had to assess their relevance, usefulness, and alignment with the user’s intent. My role included classifying each result according to strict guidelines and providing detailed feedback to explain my ratings. This work required careful analysis of linguistic nuance, content quality, and context, as well as consistency across evaluations. While not labeled as AI at the time, this process directly supports training and improving search algorithms and large language models.

2021 - 2022

Education

Work History