Max Dlott

Key Skills

Software

Scale AI

Top Subject Matter

Large Language Models

General Knowledge Domains

Reasoning and Instruction Following

Top Data Types

Text

Document

Image

Top Task Types

Bounding Box

Polygon

Segmentation

Classification

Entity (NER) Classification

Point/Key Point

Polyline

Cuboid

Object Detection

Text Generation

Question Answering

Text Summarization

Freelancer Overview

AI Training & Evaluation Specialist (Contract). Brings 16+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Scale AI and Anthropic AI Research Lab. Education includes Associate of Arts, University of Maryland Global Campus (2026) and Bachelor of Arts, The Ohio State University (2009). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI Training & Evaluation Specialist (Contract)

Scale AIText

As an AI Training & Evaluation Specialist at Scale AI, I evaluated and refined model outputs across multiple knowledge domains, ensuring strict adherence to guidelines and benchmarks. I designed domain-specific prompts to challenge and test reasoning abilities of large language models as part of high-impact research projects. Multi-dimensional rubrics were used for granular response assessment to enhance model reliability. • Evaluated language model outputs for accuracy, factual consistency, logical flow, and ethical alignment. • Crafted and applied multi-step prompts to comprehensively test AI instruction-following and reasoning. • Documented evaluation justifications in structured audit-ready language for research traceability. • Collaborated asynchronously, adapting to evolving protocols and maintaining data confidentiality.

As an AI Training & Evaluation Specialist at Scale AI, I evaluated and refined model outputs across multiple knowledge domains, ensuring strict adherence to guidelines and benchmarks. I designed domain-specific prompts to challenge and test reasoning abilities of large language models as part of high-impact research projects. Multi-dimensional rubrics were used for granular response assessment to enhance model reliability. • Evaluated language model outputs for accuracy, factual consistency, logical flow, and ethical alignment. • Crafted and applied multi-step prompts to comprehensively test AI instruction-following and reasoning. • Documented evaluation justifications in structured audit-ready language for research traceability. • Collaborated asynchronously, adapting to evolving protocols and maintaining data confidentiality.

2023 - Present

AI Data Quality Analyst (Contract)

Text

As an AI Data Quality Analyst at Anthropic AI Research Lab, I validated, annotated, and scored complex text-based model outputs for critical AI training workflows. I executed prompt-response alignment tasks and created annotations aligning outputs to nuanced instructions and research requirements. Recurring model failure modes were cataloged to proactively provide actionable feedback for model improvement. • Labeled and scored textual outputs for quality and instruction adherence using qualitative benchmarks. • Conducted annotation to support prompt engineering and model evaluation. • Refined frameworks for benchmarking reasoning, alignment, and domain-specific accuracy. • Worked asynchronously, consistently meeting project deadlines and compliance protocols.

As an AI Data Quality Analyst at Anthropic AI Research Lab, I validated, annotated, and scored complex text-based model outputs for critical AI training workflows. I executed prompt-response alignment tasks and created annotations aligning outputs to nuanced instructions and research requirements. Recurring model failure modes were cataloged to proactively provide actionable feedback for model improvement. • Labeled and scored textual outputs for quality and instruction adherence using qualitative benchmarks. • Conducted annotation to support prompt engineering and model evaluation. • Refined frameworks for benchmarking reasoning, alignment, and domain-specific accuracy. • Worked asynchronously, consistently meeting project deadlines and compliance protocols.

2022 - 2022

Education

Work History