Kyle

Key Skills

Software

Data Annotation Tech

Top Subject Matter

Polymer chemistry (synthesis, degradation, AI model evaluation)

Organic chemistry (small molecule synthesis, characterization, AI model evaluation)

Analytical chemistry (GPC, NMR, FT-IR, UV-vis)

Top Data Types

Text

Image

Document

Top Task Types

Prompt Response Writing SFT

Freelancer Overview

Chemistry Expert for AI Training – DataAnnotation. Brings 7 months of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Data Annotation Tech. Education includes Doctor of Philosophy, University of Surrey (2021) and Bachelor of Science, University of Surrey (2020). AI-training focus includes data types such as Text and labeling workflows including Prompt + Response Writing (SFT).

Labeling Experience

Chemistry Expert for AI Training – DataAnnotation

Data Annotation TechTextPrompt Response Writing SFT

As a Chemistry Expert for AI Training at DataAnnotation, I created and evaluated expert-level chemistry prompts and rubrics designed for training and assessing AI models. My work included developing complex, multi-step chemistry problems, constructing detailed evaluation rubrics, and systematically analyzing AI-generated responses for scientific accuracy and logical structure. This role required advanced scientific knowledge, data analysis skills, and the ability to communicate nuanced feedback clearly to the model training process. • Wrote over 70 hours of chemistry prompts and rubrics for AI model training and evaluation. • Developed criteria for evaluating scientific reasoning and response completeness. • Analyzed failures and weaknesses in AI model responses for structured feedback. • Covered a broad range of chemistry domains, including polymers and small molecules.

As a Chemistry Expert for AI Training at DataAnnotation, I created and evaluated expert-level chemistry prompts and rubrics designed for training and assessing AI models. My work included developing complex, multi-step chemistry problems, constructing detailed evaluation rubrics, and systematically analyzing AI-generated responses for scientific accuracy and logical structure. This role required advanced scientific knowledge, data analysis skills, and the ability to communicate nuanced feedback clearly to the model training process. • Wrote over 70 hours of chemistry prompts and rubrics for AI model training and evaluation. • Developed criteria for evaluating scientific reasoning and response completeness. • Analyzed failures and weaknesses in AI model responses for structured feedback. • Covered a broad range of chemistry domains, including polymers and small molecules.

2025 - Present

Education

Work History