Samuel W.

Key Skills

Software

Don't disclose

Top Subject Matter

LLM alignment

prompt engineering

and secure code evaluation

Top Data Types

Text

Document

Top Task Types

Entity (NER) Classification

Text Generation

Transcription

Prompt + Response Writing (SFT)

Freelancer Overview

With a degree in Information Technology and experience as a Full-Stack Developer, my skills in AI training data are rooted in advanced code assessment, adversarial red-teaming, and adjustment of model outputs. I possess hands-on experience incorporating OpenAI models into web applications, which has provided me with profound understanding of prompt engineering, function invocation, and structured JSON output verification. This technical basis allows me to generate high-quality Supervised Fine-Tuning (SFT) data and execute accurate Reinforcement Learning from Human Feedback (RLHF). Instead of merely spotting superficial mistakes, I concentrate on examining the foundational algorithmic reasoning, detecting runtime syntax errors, and evaluating code security risks in Python, JavaScript, and PHP. What distinguishes me as an AI Trainer is my capacity to convert intricate technical diagnostics into clear, logically organized explanations. I am skilled at analyzing complex multi-turn model interactions, evaluating stringent formatting requirements, and spotting edge cases overlooked by automated systems. Regardless of assessing code accuracy or evaluating responses for precision, I consistently provide thoroughly reasoned explanations that instruct language models on logical thinking, enhancing performance, and following human standards. Education includes Bachelor of Science, University of Kirinyaga. AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Evaluation and Rating.

Labeling Experience

Education

Work History