Collins Yator

Key Skills

Software

Appen

Top Subject Matter

Large Language Models

Nlp Domain Expertise

AI Safety

Top Data Types

Text

Top Task Types

Prompt Response Writing SFT

Freelancer Overview

Freelance AI Data Trainer & Annotator. Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Appen, Internal, and Proprietary Tooling. Education includes Bachelor of Science, N/A (2023). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

Prompt Engineering Experiments

TextPrompt Response Writing SFT

I developed and tested a prompt library of over 200 scenarios to assess LLMs’ robustness to ambiguous instructions, cultural edge cases, and safety boundaries. My work focused on writing, refining, and challenging prompt/response pairs for systematic evaluation. The project contributed to surfacing model weaknesses and gaps in safe, inclusive LLM behavior. • Built prompt sets targeting ambiguity and edge-case instructions. • Evaluated LLM performance on culturally sensitive and safety-critical prompts. • Systematically documented and analyzed prompt/response output variations. • Identified limitations and bias in LLM handling of diverse instructions.

I developed and tested a prompt library of over 200 scenarios to assess LLMs’ robustness to ambiguous instructions, cultural edge cases, and safety boundaries. My work focused on writing, refining, and challenging prompt/response pairs for systematic evaluation. The project contributed to surfacing model weaknesses and gaps in safe, inclusive LLM behavior. • Built prompt sets targeting ambiguity and edge-case instructions. • Evaluated LLM performance on culturally sensitive and safety-critical prompts. • Systematically documented and analyzed prompt/response output variations. • Identified limitations and bias in LLM handling of diverse instructions.

2023 - Present

LLM Response Evaluation (Personal Project)

Text

I independently conducted structured evaluations of over 500 AI chatbot outputs for accuracy, relevance, and appropriateness. Each response was reviewed with detailed criteria spanning coding, creative writing, factual questions, and ethical dilemmas. Findings were logged using spreadsheets to inform model improvements. • Assessed chatbot responses for correctness and appropriateness. • Evaluated model behavior in programming, creative, factual, and ethical scenarios. • Used spreadsheets for logging and rating LLM performance. • Generated insights to improve chatbot safety and output quality.

I independently conducted structured evaluations of over 500 AI chatbot outputs for accuracy, relevance, and appropriateness. Each response was reviewed with detailed criteria spanning coding, creative writing, factual questions, and ethical dilemmas. Findings were logged using spreadsheets to inform model improvements. • Assessed chatbot responses for correctness and appropriateness. • Evaluated model behavior in programming, creative, factual, and ethical scenarios. • Used spreadsheets for logging and rating LLM performance. • Generated insights to improve chatbot safety and output quality.

2023 - Present

Freelance AI Data Trainer & Annotator

AppenText

As a freelance AI Data Trainer & Annotator, I evaluated, ranked, and labeled AI-generated text responses across diverse natural language processing tasks. I wrote and refined prompts, provided structured written feedback, and participated in red-teaming and RLHF tasks targeting the safety, accuracy, and cultural sensitivity of LLM outputs. Datasets covered sentiment analysis, intent classification, and named entity recognition for various AI platforms. • Rated AI chatbot responses for quality, helpfulness, and safety across a wide range of topics. • Labeled and classified text data for NLP tasks such as sentiment, intent, and entity recognition. • Contributed to identifying unsafe or harmful outputs through red-teaming activities. • Used annotation platforms such as Label Studio, Scale AI, and Appen, consistently achieving a 95%+ task acceptance rate.

As a freelance AI Data Trainer & Annotator, I evaluated, ranked, and labeled AI-generated text responses across diverse natural language processing tasks. I wrote and refined prompts, provided structured written feedback, and participated in red-teaming and RLHF tasks targeting the safety, accuracy, and cultural sensitivity of LLM outputs. Datasets covered sentiment analysis, intent classification, and named entity recognition for various AI platforms. • Rated AI chatbot responses for quality, helpfulness, and safety across a wide range of topics. • Labeled and classified text data for NLP tasks such as sentiment, intent, and entity recognition. • Contributed to identifying unsafe or harmful outputs through red-teaming activities. • Used annotation platforms such as Label Studio, Scale AI, and Appen, consistently achieving a 95%+ task acceptance rate.

2023 - Present

Education

Work History