Ajay K.

Key Skills

Software

CVAT

Label Studio

Other

Top Subject Matter

AI training workflows and data annotation quality review

Structured workflow development for AI/data labeling support

Legal Services & Contract Review

Top Data Types

Text

Document

Image

Top Task Types

Classification

Segmentation

Bounding Box

Data Collection

Freelancer Overview

AI annotation & technical workflow experience (self-directed). Brings 18+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Bachelor of Economics, N/A and Post Graduate Diploma in Co-operation and Business Management, N/A. AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Classification and Data Collection.

Labeling Experience

Image annotation and segmentation/QA review via annotation platforms (CVAT/Label Studio concepts)

Label StudioImageBounding Box

The candidate applies bounding box and object labeling practices as part of structured digital data review. They conduct attention-to-detail QA by detecting visual defects, surface irregularities, and label mismatches. They ensure accurate and consistent outcomes across repetitive quality-focused image review tasks. • Bounding boxes and object labeling for defect-oriented review • Structured QA to detect inconsistencies and surface irregularities • Maintains accuracy and consistency across repeated review cycles • Learns and adapts quickly to annotation platforms and browser-based tools

2020 - Present

AI Annotation Specialist / AI workflow specialist (image annotation, segmentation, and QA review)

CVATImageSegmentation

The candidate performs image annotation work with a focus on segmentation, bounding boxes, and object labeling. They review and correct pre-annotations while following detailed project guidelines to maintain consistent labeling. They identify visual defects and inconsistencies such as missing labels and incorrect classifications during structured digital reviews. • Segmentation and object labeling including classification and annotation QA review • Review and correction of pre-annotations using project rules • Defect-oriented visual inspection (scratches, cracks, discoloration, blemishes) • QA-driven identification of missing labels, inconsistencies, and incorrect classifications

2020 - Present

AI annotation & technical workflow experience (self-directed)

TextClassification

Worked with AI-related workflows and structured digital review processes focused on annotation concepts. The work emphasized segmentation, object labeling, and quality review patterns as part of controlled annotation pipelines. Performed detail-oriented computer-based tasks requiring accuracy, consistency, and logical reasoning. • Segmentation and object labeling concepts for structured reviews • Quality review and consistency checks for annotated outputs • Used Excel and backend/CMS-style systems to support structured digital environments • Applied logical reasoning and accuracy requirements to computer-based annotation tasks

2013 - Present

Structured digital workflows and backend integrations to support AI workflow execution

OtherData Collection

Built and maintained business-focused digital systems involving structured workflows and backend integrations that align with data preparation and annotation support activities. The experience included designing structured user interactions and operational business functionality that can be used to support data labeling processes. Demonstrated comfort with modern JavaScript frameworks and technical problem solving in workflow automation contexts. • Designed structured digital workflows and backend-integrated application behavior • Supported reliable operations for workflow-driven data handling • Implemented components using JavaScript/TypeScript ecosystems • Applied technical troubleshooting to maintain consistent workflow execution

2010 - Present

AI Training & Data Labeling (within AI/emerging technologies capability described in resume)

TextClassification

You provided AI training and data labeling/annotation support as part of AI-related workflows. Your work focused on preparing and structuring labeled data to enable downstream AI use cases. You also supported research and automation tasks to improve labeling and training effectiveness.•Performed data labeling and annotation as part of AI training workflows.•Contributed to organizing labeled datasets for AI-related tasks.•Supported technology research to refine labeling approaches.•Helped drive automation workflows to improve labeling efficiency.

2020 - 2021

Education

Work History