Jake Dicks

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Label Types

Classification

Question Answering

Emotion Recognition

Text Summarization

Evaluation Rating

Entity Ner Classification

RLHF

Prompt Response Writing SFT

Freelancer Overview

I am a detail-oriented professional with hands-on experience in data annotation and AI language training. My work has involved analyzing and evaluating large datasets, fact-checking both numerical and natural language data, and validating JSON outputs to ensure accuracy and structural correctness. I am skilled at reviewing and quality-checking peer submissions, following detailed guidelines, and testing large language model outputs against defined criteria. With a strong background in data handling, Microsoft and Google Office tools, and a research-focused academic foundation, I excel at maintaining high standards of accuracy and reliability in data-driven environments. I am comfortable working independently, quickly learning new processes, and adapting to structured workflows to support the development of reliable AI systems.

Labeling Experience

Data Annotator

Scale AITextEntity Ner ClassificationRLHF

Worked on creating and structuring prompts and responses for large language models (LLMs) to improve language understanding and emotional detection capabilities. Analysed large text datasets to ensure accurate entity classification, including handling complex language styles and ambiguous phrasing. Evaluated and ranked LLM outputs against defined criteria, including grammar, spelling, factual accuracy, and relevance to the subject matter.

Worked on creating and structuring prompts and responses for large language models (LLMs) to improve language understanding and emotional detection capabilities. Analysed large text datasets to ensure accurate entity classification, including handling complex language styles and ambiguous phrasing. Evaluated and ranked LLM outputs against defined criteria, including grammar, spelling, factual accuracy, and relevance to the subject matter.

2022 - 2024

Data Annotator

Scale AITextClassificationQuestion Answering

Contributed to the evaluation and improvement of large language models by analysing and annotating large-scale text and structured data. The project focused on improving model performance in understanding language, emotion, intent, and task-specific outputs across varied use cases. Measured by very strict guidelines and required the highest accuracy to remain on the platform.

Contributed to the evaluation and improvement of large language models by analysing and annotating large-scale text and structured data. The project focused on improving model performance in understanding language, emotion, intent, and task-specific outputs across varied use cases. Measured by very strict guidelines and required the highest accuracy to remain on the platform.

2022 - 2024

Education

Work History