Maxwell Liebler

Key Skills

Software

Mercor

Snorkel AI

Other

Top Subject Matter

AI/LLM Evaluation and Visual Design

Workflow and Process Data Labeling

LLM Training and Question Dataset Creation

Top Data Types

Text

Audio

Image

Top Task Types

Classification

Prompt + Response Writing (SFT)

Audio Recording

Data Collection

Freelancer Overview

Generalist / Visual design expert / Audio model trainer. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Mercor, Meta, and Snorkel AI. Education includes Bachelor of Arts, University of Oregon (2022). AI-training focus includes data types such as Text and Audio and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Generalist / Visual design expert / Audio model trainer

MercorText

At Mercor, I labeled and graded Large Language Model (LLM) outputs based on various criteria. My work involved identifying and correcting errors, adding missing details, and enhancing output clarity. I also examined and classified text elements such as fonts into different subcategories. • Evaluated LLM outputs for quality and accuracy. • Enhanced text clarity and added details as needed. • Classified text font elements into subcategories. • Used internal or proprietary software as part of the evaluation process.

At Mercor, I labeled and graded Large Language Model (LLM) outputs based on various criteria. My work involved identifying and correcting errors, adding missing details, and enhancing output clarity. I also examined and classified text elements such as fonts into different subcategories. • Evaluated LLM outputs for quality and accuracy. • Enhanced text clarity and added details as needed. • Classified text font elements into subcategories. • Used internal or proprietary software as part of the evaluation process.

2025 - Present

UX researcher (Audio data collection)

OtherAudioData Collection

As a UX researcher for Exponent, I collected and managed voice and audio data in diverse real-world environments. I coordinated with venues to optimize the data gathering process and simulated various everyday scenarios for audio quality and clarity optimization. The study focused on improving user experiences using real audio data from restaurants, grocery stores, workplaces, and gyms. • Gathered voice and ambient audio data at multiple locations. • Managed logistical setup for venue-based audio collection. • Simulated user interactions for more authentic data. • Used Exponent's internal data tools for collection and processing.

As a UX researcher for Exponent, I collected and managed voice and audio data in diverse real-world environments. I coordinated with venues to optimize the data gathering process and simulated various everyday scenarios for audio quality and clarity optimization. The study focused on improving user experiences using real audio data from restaurants, grocery stores, workplaces, and gyms. • Gathered voice and ambient audio data at multiple locations. • Managed logistical setup for venue-based audio collection. • Simulated user interactions for more authentic data. • Used Exponent's internal data tools for collection and processing.

2025 - 2025

Data labeling analyst

TextClassification

At Meta, I performed data labeling tasks focused on workflow and guideline adherence. I labeled workflows and incorporated process changes as directed by cross-functional teams. I also collaborated with vendors to resolve data obstacles and bugs. • Labeled data and workflows quickly according to guidelines. • Helped vendors overcome workflow and data issues. • Applied changes to labeling processes as needed. • Used internal or proprietary software for data labeling.

At Meta, I performed data labeling tasks focused on workflow and guideline adherence. I labeled workflows and incorporated process changes as directed by cross-functional teams. I also collaborated with vendors to resolve data obstacles and bugs. • Labeled data and workflows quickly according to guidelines. • Helped vendors overcome workflow and data issues. • Applied changes to labeling processes as needed. • Used internal or proprietary software for data labeling.

2025 - 2025

AI model trainer

AudioAudio Recording

At AccunAI, I trained AI models using voice command datasets for LLM applications. My primary focus was on creating voice data ensuring that adjectives aligned with the intended command tone. I followed rigorous deadlines and quality standards for all audio labeling and data entry. • Recorded and annotated voice commands for AI use. • Maintained adjective and tone consistency throughout entries. • Adhered to strict quality and deadline requirements. • Used AccunAI’s internal data annotation or audio labeling platform.

At AccunAI, I trained AI models using voice command datasets for LLM applications. My primary focus was on creating voice data ensuring that adjectives aligned with the intended command tone. I followed rigorous deadlines and quality standards for all audio labeling and data entry. • Recorded and annotated voice commands for AI use. • Maintained adjective and tone consistency throughout entries. • Adhered to strict quality and deadline requirements. • Used AccunAI’s internal data annotation or audio labeling platform.

2024 - 2024

AI data trainer

Snorkel AITextPrompt Response Writing SFT

As an AI data trainer for Snorkel AI, I created and reviewed diverse prompt and question datasets for LLM training. I ensured all created questions and answers met strict quality and guideline standards. The role required intensive research and attention to detail across various subject matters. • Authored questions for AI model inputs. • Reviewed datasets for compliance and accuracy. • Conducted research for detailed LLM training content. • Utilized Snorkel AI's proprietary or internal labeling software.

As an AI data trainer for Snorkel AI, I created and reviewed diverse prompt and question datasets for LLM training. I ensured all created questions and answers met strict quality and guideline standards. The role required intensive research and attention to detail across various subject matters. • Authored questions for AI model inputs. • Reviewed datasets for compliance and accuracy. • Conducted research for detailed LLM training content. • Utilized Snorkel AI's proprietary or internal labeling software.

2024 - 2024

Education

Work History