Karyn K.

Key Skills

Software

Appen

Top Subject Matter

Machine learning datasets for NLP

computer vision

and audio

Top Data Types

Image

Video

Text

Document

Top Task Types

Object Detection

Entity (NER) Classification

Freelancer Overview

Data Annotator for CrowdGen/Appen (remote). Brings 10+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Appen, Internal, and Proprietary Tooling. Education includes Associate of Arts, Lorain County Community College. AI-training focus includes data types such as Image, Video, and Text and labeling workflows including Object Detection and Entity (NER) Classification.

Labeling Experience

Data Annotator for CrowdGen/Appen (remote)

AppenImageObject Detection

Provided multi-domain data annotation support for NLP, computer vision, and audio projects with a focus on producing guideline-compliant labeled outputs. Annotated visual content including images and video using bounding boxes, polygons, keypoints, and segmentation masks to identify objects and spatial relationships. Ensured labeled data quality through consistent adherence to project standards across varying toolchains. • Labeled images and video with bounding boxes, polygons, keypoints, and segmentation masks • Applied annotation guidelines to identify objects, actions, and spatial relationships • Adapted quickly to multiple proprietary and commercial annotation tools/workflows • Supported a range of dataset creation needs across NLP, vision, and audio domains

2021 - Present

Data Annotator & QC for Datavio/iSoftStone (remote)

TextEntity (NER) Classification

Served as a primary NLP annotator for an automotive smart-assistant dataset, producing and annotating large volumes of natural-language utterances across multiple domains. Performed annotation work using complex, guideline-driven requirements with an emphasis on achieving high accuracy. In addition to annotation, completed quality control review by checking outputs, correcting errors, and reporting performance metrics. • Wrote and annotated over 250,000 natural-language utterances • Achieved 99% accuracy on annotated utterances • Conducted team QC: review, error correction, and performance reporting • Contributed to additional NLP projects with proprietary annotation tools

2017 - Present

Data Annotator & Curator for BankruptcyWatch (remote)

DocumentEntity (NER) Classification

Annotated and curated legal and business data to support structured extraction from documentation. Used INCEpTION NLP annotation software to identify and tag business entities and contact information based on detailed research. Applied domain knowledge of U.S. legal documents and procedures to label bankruptcy case dockets with entity-focused annotations. • Tagged business entities and contact information after in-depth research • Annotated bankruptcy case dockets using domain-specific context • Curated legal/business records to create usable labeled datasets • Performed entity labeling via INCEpTION NLP annotation workflow

2022 - 2024

Education

Work History