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V

Vedant Pandey

AI Systems Developer and Model Trainer (data and research scientist)

INDIA flag
delhi, India
$40.00/hrIntermediateCloudfactoryCrowdsourceData Annotation Tech

Key Skills

Software

CloudFactoryCloudFactory
CrowdSourceCrowdSource
Data Annotation TechData Annotation Tech
DataloopDataloop
DatatureDatature
Google Cloud Vertex AIGoogle Cloud Vertex AI
iMeritiMerit
Kili TechnologyKili Technology
LabelboxLabelbox
MercorMercor
Micro1
MindriftMindrift
OpenCV AI Kit (OAK)OpenCV AI Kit (OAK)
PlaymentPlayment
Redbrick AIRedbrick AI
RoboflowRoboflow
Scale AIScale AI
SuperAnnotateSuperAnnotate
SlothSloth
Snorkel AISnorkel AI

Top Subject Matter

health
finance
e commerce

Top Data Types

ImageImage
VideoVideo
AudioAudio

Top Task Types

Fine Tuning
RLHF
Prompt Response Writing SFT
Bounding Box
Polygon
Segmentation
Classification
Object Detection
Text Generation
Question Answering
Text Summarization
Transcription
Data Collection

Freelancer Overview

AI Systems Developer and Model Trainer (Truvo). 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 Technology, VIT Bhopal University (2025). AI-training focus includes data types such as Text and labeling workflows including Fine-tuning, Evaluation, and Rating.

IntermediateEnglish

Labeling Experience

LLM Pipeline Architect / Model Evaluator

Text
Engineered a multi-LLM data processing pipeline and intelligent submission analysis system leveraging annotated structured data. Set up contextual re-scoring and output evaluation strategies based on human and automated annotations. Designed workflows that synchronize annotated evaluation with CRM tracking for continuous model quality improvement. • Conducted human-in-the-loop annotation and validation of model-generated outputs. • Implemented rating and re-scoring mechanisms to assess contextual appropriateness and accuracy of LLM submissions. • Integrated annotation results into automated performance tracking systems. • Leveraged feedback to fine-tune model recommendations and decision support processes.

Engineered a multi-LLM data processing pipeline and intelligent submission analysis system leveraging annotated structured data. Set up contextual re-scoring and output evaluation strategies based on human and automated annotations. Designed workflows that synchronize annotated evaluation with CRM tracking for continuous model quality improvement. • Conducted human-in-the-loop annotation and validation of model-generated outputs. • Implemented rating and re-scoring mechanisms to assess contextual appropriateness and accuracy of LLM submissions. • Integrated annotation results into automated performance tracking systems. • Leveraged feedback to fine-tune model recommendations and decision support processes.

2025 - 2025

AI Systems Developer and Model Trainer (Truvo)

TextFine Tuning
Designed, trained, and integrated multimodal AI models using labeled voice, text, and structured data for intelligent automation. Developed data pipelines and evaluation frameworks that required preparing, curating, and processing training datasets for model development. Evaluated model performance and retrained models based on annotated outputs from multiple data sources. • Labeled and prepared training data across voice, text, and structured data domains for AI model development. • Integrated feedback-driven annotation cycles for model tuning and improvement. • Evaluated output quality by benchmarking against annotated ground truth. • Applied fine-tuning techniques to enhance contextual understanding and prediction in operational AI models.

Designed, trained, and integrated multimodal AI models using labeled voice, text, and structured data for intelligent automation. Developed data pipelines and evaluation frameworks that required preparing, curating, and processing training datasets for model development. Evaluated model performance and retrained models based on annotated outputs from multiple data sources. • Labeled and prepared training data across voice, text, and structured data domains for AI model development. • Integrated feedback-driven annotation cycles for model tuning and improvement. • Evaluated output quality by benchmarking against annotated ground truth. • Applied fine-tuning techniques to enhance contextual understanding and prediction in operational AI models.

2025 - 2025

Education

V

VIT Bhopal University

Master of Technology, Computer Science and Engineering in Artificial Intelligence and Machine Learning

Master of Technology
2020 - 2025

Work History

T

TheAgentic

AI Researcher

San Francisco
2025 - Present
A

ADG Online Solution Pvt. Ltd.

AI/Python Developer

Delhi
2025 - 2025