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Kayleigh Sengupta

Kayleigh Sengupta

AI Generalist - Multimodal Video Data Annotation & Evaluation

UNITED_KINGDOM flag
Portsmouth, United Kingdom
Intermediate

Key Skills

Software

No software listed

Top Subject Matter

Multimodal AI Model Evaluation and Annotation

Top Data Types

VideoVideo
ImageImage

Top Label Types

Entity Ner Classification

Freelancer Overview

AI Generalist - Multimodal Video Data Annotation & Evaluation. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Master of Science, University of Portsmouth (2025). AI-training focus includes data types such as Video and labeling workflows including Entity (NER) Classification.

Intermediate

Labeling Experience

AI Generalist - Multimodal Video Data Annotation & Evaluation

VideoEntity Ner Classification
As an AI Generalist at Aether Project, I performed multimodal annotation on video data with a focus on Named Entity Recognition (NER) and relationship annotation utilizing structured schemas. I conducted qualitative and stylistic evaluations for vision models by comparing outputs and referencing artistic style criteria. My work involved object-level editing on video and image data to ensure precision and quality for downstream model training tasks. • Tagged entities and relationships for NER and contextual annotation across dynamic video content. • Conducted vision model evaluations to assess quality, relevance, and output consistency. • Completed video artistic style reference tasks and object-level editing (e.g., furniture removal). • Ensured guideline adherence, ethical data handling, and provided actionable feedback for model improvement.

As an AI Generalist at Aether Project, I performed multimodal annotation on video data with a focus on Named Entity Recognition (NER) and relationship annotation utilizing structured schemas. I conducted qualitative and stylistic evaluations for vision models by comparing outputs and referencing artistic style criteria. My work involved object-level editing on video and image data to ensure precision and quality for downstream model training tasks. • Tagged entities and relationships for NER and contextual annotation across dynamic video content. • Conducted vision model evaluations to assess quality, relevance, and output consistency. • Completed video artistic style reference tasks and object-level editing (e.g., furniture removal). • Ensured guideline adherence, ethical data handling, and provided actionable feedback for model improvement.

2025 - Present

Education

U

University of Portsmouth

Master of Science, Environmental Science: Crisis and Disaster Management

Master of Science
2023 - 2025

Work History

F

Flow Pundits Ltd

Project Manager

Portsmouth
2025 - Present