Shuntoria Reid

As an AI Trainer and AI Model Evaluation professional with a Bachelor of Science in Computer Science, I specialize in enhancing large language models and optimizing their performance through human feedback. Leveraging expertise in Python, R, and a suite of AI/ML technologies, I build robust validation processes, identify model errors, and translate complex technical findings into clear, actionable feedback. Currently pursuing a Bachelor of Science in Computer Science at Full Sail University, I am committed to expanding my knowledge in applied AI, model evaluation, prompt engineering, and responsible AI development.

I am seeking opportunities in AI training, LLM evaluation, prompt engineering, model quality, AI data operations, and junior applied AI development.

Computer Science Expert at Handshake AI (2025-01 – Present)

Contributed to enhancing Large Language Models (LLMs) by developing domain-specific prompts and evaluating AI-generated responses. Participated in AI research projects, leveraging expertise in computer science to improve LLM capabilities and explore new applications.

• Developed and evaluated domain-specific prompts for Large Language Models across STEM and coding tasks, enhancing model accuracy and relevance.
• Rewrote and refined AI-generated responses, particularly in STEM fields, to ensure factual accuracy and clarity, significantly improving output quality.
• Analyzed and refined complex software codebases, and drafted coding prompts to evaluate and improve AI model responses for technical accuracy and efficiency.

Gen AI Engineer at Randstad (2023-01 – 2026-03)

Participated in the full lifecycle of Gen AI model development and deployment, from data extraction and preparation to model testing and validation. Collaborated with business and technology teams to translate requirements into actionable models, ensuring data quality and performance optimization.

• Developed and deployed RAG-powered enterprise document assistants and LLM-driven customer support chatbots, enhancing information retrieval and automating user inquiries.
• Designed and implemented AI agents for automating routine operations and internal processes, including email drafting, task scheduling, and workflow planning, significantly improving efficiency.
• Participated in comprehensive model testing and validation processes, optimizing algorithm selection based on statistical and business metrics, and ensuring data quality for robust model development.

AI Prompt Engineer at Sepal AI (2016-01 – 2022-12)

Designed, optimized, and evaluated prompts for diverse AI models (LLMs, image models) to enhance performance. Analyzed outputs, conducted A/B testing, and refined prompts. Mitigated AI response issues like edge cases, bias, and hallucinations for improved reliability.

• Designed, tested, and refined prompts for diverse AI models (LLMs, image models) to optimize performance, enhance accuracy, and ensure relevance of AI-generated outputs.
• Analyzed AI-generated outputs and enhanced prompt performance, conducting A/B testing and performance evaluations to ensure accuracy and relevance.
• Identified and mitigated edge cases, bias, hallucinations, and inconsistencies in AI responses to improve model reliability and user trust.

Bachelor's Degree in Computer Science – Full Sail University (2018-03 – 2023-05)