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Anurag Parsi

Anurag Parsi

GenAI/LLM Data Labeling & Prompt Engineering

USA flagN/A, Usa
$25.00/hrExpertAws SagemakerCloudfactory

Key Skills

Software

AWS SageMakerAWS SageMaker
CloudFactoryCloudFactory

Top Subject Matter

Llms Domain Expertise
Prompt Engineering
Generative AI

Top Data Types

TextText
DocumentDocument

Top Task Types

Fine-tuningFine-tuning
Text GenerationText Generation
Question AnsweringQuestion Answering
Text SummarizationText Summarization
Data CollectionData Collection
Prompt + Response Writing (SFT)Prompt + Response Writing (SFT)
ClassificationClassification
SegmentationSegmentation
Computer Programming/CodingComputer Programming/Coding
Evaluation/RatingEvaluation/Rating
Function CallingFunction Calling

Freelancer Overview

GenAI/LLM Data Labeling & Prompt Engineering. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Data Labeling/AI Training, Internal and Proprietary Tooling. Education includes Master of Science, New England College (2022). AI-training focus includes data types such as Text and labeling workflows including Fine-tuning.

ExpertEnglishTeluguHindi

Labeling Experience

GenAI/LLM Data Labeling & Prompt Engineering

TextFine Tuning
As a Data Scientist at Verizon, I contributed to prompt engineering, fine-tuning, and evaluation for LLM-based GenAI tools. My responsibilities included prompt design for classification, summarization, and information extraction, as well as tuning OpenAI models and optimizing context-aware prompt chains. I processed and indexed unstructured data, including PDFs, images, and chat transcripts, for ingestion into LLM pipelines. • Fine-tuned and evaluated prompts for LLMs to enhance GenAI tool performance • Processed and labeled unstructured data, such as documents and chat logs • Used OCR and unstructuredPDFLoader tools to prepare diverse data types for model training • Tuned and optimized OpenAI models and prompt chains for contextual LLM interactions

As a Data Scientist at Verizon, I contributed to prompt engineering, fine-tuning, and evaluation for LLM-based GenAI tools. My responsibilities included prompt design for classification, summarization, and information extraction, as well as tuning OpenAI models and optimizing context-aware prompt chains. I processed and indexed unstructured data, including PDFs, images, and chat transcripts, for ingestion into LLM pipelines. • Fine-tuned and evaluated prompts for LLMs to enhance GenAI tool performance • Processed and labeled unstructured data, such as documents and chat logs • Used OCR and unstructuredPDFLoader tools to prepare diverse data types for model training • Tuned and optimized OpenAI models and prompt chains for contextual LLM interactions

2024 - Present

Education

N

New England College

Master of Science, Data Science

Master of Science
2022 - 2024

Work History

V

Verizon

Data Scientist

N/A
2024 - Present
A

Aadhyam Solutions Private Limited

Data Scientist

N/A
2020 - 2024