Tarisa Salsabila

Key Skills

Software

Appen

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Top Data Types

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Text

Top Task Types

Classification

Evaluation Rating

Prompt Response Writing SFT

Text Generation

Text Summarization

Freelancer Overview

I am an AI training and data labeling specialist with hands-on experience in large language model (LLM) evaluation projects, including prompt creation and rating AI-generated outputs. My work involves assessing response quality, relevance, coherence, and appropriateness across diverse topics to improve natural language processing systems. I have worked on various platforms such as Appen and Welocalize, contributing to projects focused on content moderation, search and ad evaluation, and prompt-response alignment for generative AI. In addition to LLM evaluation, I am familiar with classification, ranking, and annotation tasks related to digital advertising, content safety, and user intent. My attention to detail, critical thinking, and adaptability allow me to deliver accurate and consistent annotations. I am passionate about contributing to the development of ethical and efficient AI systems that impact real-world applications across industries.

Labeling Experience

LLM Prompt Writing & AI Response Evaluation

AppenTextClassificationText Generation

In this project, I contributed to the development and fine-tuning of large language models by generating diverse prompts and evaluating AI-generated responses. Tasks included writing high-quality prompts across various domains, assessing response accuracy, coherence, and helpfulness, and ranking multiple outputs based on specific guidelines. I also flagged harmful, biased, or irrelevant content to ensure adherence to safety and ethical standards. The project required strong judgment, consistency, and attention to nuanced differences in language. All tasks were completed on Appen’s internal platform with strict quality and throughput metrics.

In this project, I contributed to the development and fine-tuning of large language models by generating diverse prompts and evaluating AI-generated responses. Tasks included writing high-quality prompts across various domains, assessing response accuracy, coherence, and helpfulness, and ranking multiple outputs based on specific guidelines. I also flagged harmful, biased, or irrelevant content to ensure adherence to safety and ethical standards. The project required strong judgment, consistency, and attention to nuanced differences in language. All tasks were completed on Appen’s internal platform with strict quality and throughput metrics.

2023 - 2024

Education

Work History