Matthew Feinberg

Key Skills

Software

Scale AI

Other

Labelbox

Google Cloud Vertex AI

Top Subject Matter

LLM Training

Reasoning Domain Expertise

AI Safety

Top Data Types

Text

Video

Document

Top Task Types

RLHF

Classification

Red Teaming

Freelancer Overview

Senior Data Operations Specialist (SME). Brings 18+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Scale AI, Other, and Labelbox. Education includes Bachelor of Science, California State University, Long Beach (2003) and High School Diploma, Huntington Beach High School (1999). AI-training focus includes data types such as Text and Multimodal Data and labeling workflows including RLHF, Classification, and Red Teaming.

Labeling Experience

Senior Data Operations Specialist (SME)

Scale AITextRLHF

As a Senior Data Operations Specialist (SME) at Scale AI/DataAnnotation.tech, I led technical LLM training focused on complex reasoning, safety, and factual accuracy. My work included ranking, rating, and annotating large volumes of AI model outputs, and performing high-level audits for quality assurance. I contributed to drafting project guidelines and developing 'Red Teaming' processes to identify and mitigate risks in AI safety protocols. • Ranked and rated thousands of model outputs for helpfulness and harmlessness. • Led audits and peer reviews to reduce labeling error rates. • Drafted comprehensive labeling and safety evaluation guidelines. • Specialized in multi-step technical verification for LLMs.

As a Senior Data Operations Specialist (SME) at Scale AI/DataAnnotation.tech, I led technical LLM training focused on complex reasoning, safety, and factual accuracy. My work included ranking, rating, and annotating large volumes of AI model outputs, and performing high-level audits for quality assurance. I contributed to drafting project guidelines and developing 'Red Teaming' processes to identify and mitigate risks in AI safety protocols. • Ranked and rated thousands of model outputs for helpfulness and harmlessness. • Led audits and peer reviews to reduce labeling error rates. • Drafted comprehensive labeling and safety evaluation guidelines. • Specialized in multi-step technical verification for LLMs.

2022 - Present

Google Cloud Generative AI Fundamentals

Google Cloud Vertex AITextClassification

I completed the Generative AI Fundamentals certification from Google Cloud, focusing on foundational aspects of large language model training and evaluation workflows. Through this program, I gained exposure to data labeling strategies used for generative AI and LLM applications. Emphasis was placed on understanding prompt engineering and classification techniques for high-quality dataset creation. • Learned data labeling and evaluation best practices for LLMs. • Applied prompt + response curation methods in training scenarios. • Engaged with case studies involving text classification and safety checks. • Practiced dataset preparation and fine-tuning for generative AI models.

I completed the Generative AI Fundamentals certification from Google Cloud, focusing on foundational aspects of large language model training and evaluation workflows. Through this program, I gained exposure to data labeling strategies used for generative AI and LLM applications. Emphasis was placed on understanding prompt engineering and classification techniques for high-quality dataset creation. • Learned data labeling and evaluation best practices for LLMs. • Applied prompt + response curation methods in training scenarios. • Engaged with case studies involving text classification and safety checks. • Practiced dataset preparation and fine-tuning for generative AI models.

2025 - 2025

Labelbox Academy Data Annotation Masterclass

LabelboxClassification

I completed a Data Annotation & Labeling Masterclass at Labelbox Academy that covered fundamental and advanced annotation techniques for multimodal datasets. The course provided hands-on training in using the Labelbox platform for text, image, and video annotation scenarios. Key modules included developing high-quality classification datasets and error analysis. • Practiced image, text, and video annotation using Labelbox tools. • Performed classification and validation tasks across sample datasets. • Conducted quality checks and iterative dataset improvements. • Learned standard operating procedures for scalable annotation pipelines.

I completed a Data Annotation & Labeling Masterclass at Labelbox Academy that covered fundamental and advanced annotation techniques for multimodal datasets. The course provided hands-on training in using the Labelbox platform for text, image, and video annotation scenarios. Key modules included developing high-quality classification datasets and error analysis. • Practiced image, text, and video annotation using Labelbox tools. • Performed classification and validation tasks across sample datasets. • Conducted quality checks and iterative dataset improvements. • Learned standard operating procedures for scalable annotation pipelines.

2024 - 2024

Stanford Online - Ethical AI & Bias Mitigation

OtherTextClassification

I completed coursework in Ethical AI & Bias Mitigation from Stanford Online, with a focus on annotation strategies that promote fairness and mitigate harmful model biases. The curriculum addressed key ethical considerations in dataset curation for AI training. Practical modules included reviewing and correcting training data to align with equity standards. • Developed skills to identify bias in AI-labeled text datasets. • Practiced annotation revision for fairness and accuracy. • Participated in scenario-based training on ethical data labeling. • Reviewed guidelines for responsible AI data practices.

I completed coursework in Ethical AI & Bias Mitigation from Stanford Online, with a focus on annotation strategies that promote fairness and mitigate harmful model biases. The curriculum addressed key ethical considerations in dataset curation for AI training. Practical modules included reviewing and correcting training data to align with equity standards. • Developed skills to identify bias in AI-labeled text datasets. • Practiced annotation revision for fairness and accuracy. • Participated in scenario-based training on ethical data labeling. • Reviewed guidelines for responsible AI data practices.

2023 - 2023

DeepLearning.AI RLHF Course

OtherTextRLHF

I completed rigorous coursework on Reinforcement Learning from Human Feedback (RLHF) through DeepLearning.AI, where I learned core theories and hands-on methods for training language models. The training focused on ranking, feedback, and iterative model tuning to improve LLM behavior. This program included specialized modules on AI safety and bias mitigation. • Conducted simulated label ranking exercises with model-generated outputs. • Explored techniques for reducing bias in AI systems. • Developed feedback protocols for iterative model improvement. • Applied RLHF instruction in practical annotation workflows.

I completed rigorous coursework on Reinforcement Learning from Human Feedback (RLHF) through DeepLearning.AI, where I learned core theories and hands-on methods for training language models. The training focused on ranking, feedback, and iterative model tuning to improve LLM behavior. This program included specialized modules on AI safety and bias mitigation. • Conducted simulated label ranking exercises with model-generated outputs. • Explored techniques for reducing bias in AI systems. • Developed feedback protocols for iterative model improvement. • Applied RLHF instruction in practical annotation workflows.

2023 - 2023

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Education

Work History