Zach Williams

Key Skills

Software

Mercor

Top Subject Matter

No subject matter listed

Top Data Types

Image

Top Label Types

Prompt Response Writing SFT

Freelancer Overview

I am a detail-oriented coder with a strong background in Python, data annotation, and AI training data processes. My experience includes labeling diverse datasets—text, images, and audio—with high accuracy, as well as developing Python scripts to automate data preprocessing and quality checks. I have hands-on experience with key AI and ML tools such as TensorFlow, PyTorch, scikit-learn, and Hugging Face, and have contributed to projects ranging from chatbot fine-tuning in NLP to image classification using deep learning. I am skilled at evaluating AI model outputs, providing structured feedback, and collaborating with remote teams to meet tight deadlines. My passion for continuous learning, problem-solving, and coding efficiency drives me to deliver high-quality results in every AI data project I take on.

Labeling Experience

AI Training Data Specialist – Multi-Modal Annotation & Quality Review

MercorImagePrompt Response Writing SFT

Project Description Worked as a Data Labeling and AI Training Specialist on multiple large-scale machine learning projects involving text, image, and audio datasets. Scope of Work Included: Annotated over 50,000+ data points across text, image, and audio datasets Performed Named Entity Recognition (NER) tagging for LLM training Labeled objects using bounding boxes and segmentation tools for computer vision models Conducted sentiment and emotion recognition labeling Completed RLHF tasks including response ranking, safety evaluation, and output grading Transcribed and quality-reviewed AI audio training datasets Wrote and evaluated prompt-response pairs for supervised fine-tuning (SFT) Quality Measures Followed: Maintained 95%+ accuracy across projects Followed strict annotation guidelines and ontology frameworks Participated in inter-annotator agreement checks Conducted peer review and quality assurance validation Met tight daily/weekly production targets without compromis

Project Description Worked as a Data Labeling and AI Training Specialist on multiple large-scale machine learning projects involving text, image, and audio datasets. Scope of Work Included: Annotated over 50,000+ data points across text, image, and audio datasets Performed Named Entity Recognition (NER) tagging for LLM training Labeled objects using bounding boxes and segmentation tools for computer vision models Conducted sentiment and emotion recognition labeling Completed RLHF tasks including response ranking, safety evaluation, and output grading Transcribed and quality-reviewed AI audio training datasets Wrote and evaluated prompt-response pairs for supervised fine-tuning (SFT) Quality Measures Followed: Maintained 95%+ accuracy across projects Followed strict annotation guidelines and ontology frameworks Participated in inter-annotator agreement checks Conducted peer review and quality assurance validation Met tight daily/weekly production targets without compromis

2023 - 2025

Education

Work History