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Maxann Mucker

@maxannmucker

Message

Senior AI Training & Data Annotation Lead improving model quality through rigorous human feedback.

United States

Message

What I'm looking for

I want to lead RLHF and data-annotation programs that improve model quality through precise, bias-aware labeling, strong IAA/QA, and scalable guidelines—helping build responsible AI with measurable relevance, safety, and helpfulness gains.

I’m a results-driven Senior Data Annotation & AI Training Lead with 6+ years designing, executing, and scaling annotation pipelines across computer vision, NLP, audio/video AI, and generative AI. I’ve built and maintained guideline-driven workflows for RLHF (comparison ranking, ideal response writing, and hallucination detection) and delivered high-quality datasets through bias-aware, responsible AI human feedback.

I lead distributed annotator teams (22+), run inter-annotator agreement audits (Cohen’s Kappa) with sustained IAA above 0.88, and partner with ML engineers to improve instructions, edge-case protocols, and quality benchmarks. My impact includes reducing error rates by 34% in early implementation, improving annotation throughput by 41%, achieving 98.6% data acceptance on critical autonomous-driving bounding box work (500K+ images), and scaling search relevance evaluation across 200,000+ document pairs using NDCG-aligned scoring.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Annotation Lead

Current

Scale AI

Mar 2022 - Present (4 years 3 months)

Led a distributed team of 22 annotators across image segmentation, NLP, and RLHF projects, reducing annotation error rates by 34% in the first quarter. Managed RLHF pipelines for 50,000+ monthly model outputs, maintained sustained IAA above 0.88 (Cohen’s Kappa), and ran search relevance evaluation on 200,000+ query-document pairs.

Inter Annotator Agreement (Cohen'S Kappa)Content Moderation Hallucination Detection Search Relevance Evaluation (NDCG)Annotations Prompt Instruction QA

Data Annotation Specialist II

Lionbridge AI (TELUS International)

Aug 2019 - Feb 2022 (2 years 6 months)

Performed high-volume NLP labeling (NER, sentiment, intent classification, coreference) and collaborated with licensed radiologists to annotate medical imaging (X-rays, MRIs, CTs). Conducted content moderation for 15,000+ social posts monthly, mentored 12 junior annotators, and maintained sustained accuracy above 99% on complex labeling tasks.

Coreference Resolution OHIF Viewer Annotation QA Calibration

AI Data Analyst & Coordinator

Appen Limited

May 2018 - Jul 2019 (1 year 2 months)

Coordinated crowd-sourced annotation across 8 concurrent campaigns by managing task distribution, contributor quality monitoring, and delivery timelines. Built document AI labeling (invoice extraction, form classification, table boundary detection, OCR correction) and ran SERP search relevance evaluations, annotating 10,000+ images per sprint and reducing rework by 28% over two project cycles.

Crowdsourced Annotation Management OCR Output Correction Search Relevance Table Boundary Detection Contributor Onboarding Training

Education

Degrees, certifications, and relevant coursework

University of Texas at Austin

Master of Science, Computational Linguistics

Grade: GPA 3.91/4.0

M.S. in Computational Linguistics with a thesis focused on optimizing human feedback pipelines for low-resource NLP model training. Graduated May 2018.