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Ajay Shekhawat

Ajay Shekhawat

Freelance Data Science Consultant (Data Annotation Platform and Model Evaluation)

United Kingdom flagLondon, United Kingdom
$50.00/hrIntermediateGoogle Cloud Vertex AIInternal Proprietary Tooling

Key Skills

Software

Google Cloud Vertex AIGoogle Cloud Vertex AI
Internal/Proprietary Tooling

Top Subject Matter

AI/LLM Evaluation
Retrieval-Augmented Generation (RAG)
Enterprise Applications

Top Data Types

Computer Code ProgrammingComputer Code Programming
TextText

Top Task Types

Computer Programming Coding
Evaluation Rating
Prompt Response Writing SFT
RLHF

Freelancer Overview

Freelance Data Science Consultant (Data Annotation Platform and Model Evaluation). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

IntermediateEnglish

Labeling Experience

Freelance Data Science Consultant (Data Annotation Platform and Model Evaluation)

Text
Built an internal annotation platform integrating response generation and retrieval APIs to accelerate annotation speed and support scalable workflows. Performed evaluation and competitive analysis of RAG architectures, vector search platforms, and prompt engineering strategies for enterprise LLM applications. Analyzed and documented context chunking and prompt mechanisms to establish best practices for model evaluation and system optimization. • Created an annotation workflow focused on response generation and retrieval tasks. • Synthesized insights for engineering, product, and research decision-making. • Led evaluation efforts for large language model (LLM) responses and retrieval performance. • Improved annotation speeds by 50% via design of scalable internal tools.

Built an internal annotation platform integrating response generation and retrieval APIs to accelerate annotation speed and support scalable workflows. Performed evaluation and competitive analysis of RAG architectures, vector search platforms, and prompt engineering strategies for enterprise LLM applications. Analyzed and documented context chunking and prompt mechanisms to establish best practices for model evaluation and system optimization. • Created an annotation workflow focused on response generation and retrieval tasks. • Synthesized insights for engineering, product, and research decision-making. • Led evaluation efforts for large language model (LLM) responses and retrieval performance. • Improved annotation speeds by 50% via design of scalable internal tools.

2024 - Present

Education

L

Liverpool John Moores University

Masters, Machine Learning and AI

Masters
2022 - 2023
L

LJMU Liverpool

Master of Science, AI & Machine Learning

Master of Science
2021 - 2023

Work History

C

Contextual AI

Freelance Data Science Consultant

London
2024 - Present
A

AB Inbev

Data Scientist

Bangalore
2021 - 2024