Saivivek Kunta

Key Skills

Software

AWS SageMaker

Appen

CrowdSource

Data Annotation Tech

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Image

Text

Top Task Types

Classification

Evaluation/Rating

Question Answering

Text Generation

Text Summarization

Transcription

Freelancer Overview

I am a data scientist and ML engineer with hands-on experience in data labeling, annotation, and AI training data workflows. At Amazon, I have contributed to over 10 critical machine learning projects, working extensively with structured and unstructured data—images, text, audio, and video—to support model development in domains such as NLP, generative AI, and computer vision. My expertise includes performing high-accuracy tasks like bounding box annotation, segmentation, classification, and transcription, always ensuring data quality through rigorous validation and adherence to guidelines. I am skilled in Python, SQL, AWS SageMaker Ground Truth, Appen, and QuickSight, and have a proven track record of collaborating with data science teams to improve dataset accuracy and model performance. I thrive in fast-paced environments, consistently meeting tight deadlines while maintaining the highest standards for data integrity and operational efficiency.

Labeling Experience

Autonomous Business Intelligence using Agentic AI

DocumentQuestion Answering

Skills Used: Python, OpenAI GPT, LangChain, Multi-Agent, Azure OpenAI, Vector DB, Prompt Engineering, Agentic AI, RAG, Semantic Search Roles & Responsibilities: Architected and developed an autonomous business intelligence platform using multi-agent AI architecture. Designed specialized AI agents for data analysis, reporting, and strategic recommendation generation. Implemented autonomous workflows using LangChain and OpenAI GPT models for intelligent data interpretation. Built an automated report generation system capable of producing business insights from structured data. Developed an AI-driven insight discovery system to detect trends, anomalies, and business opportunities. Created a strategic recommendation engine that suggests actionable business decisions. Applied advanced prompt engineering techniques to improve accuracy and contextual understanding. Integrated vector databases for knowledge retrieval and contextual reasoning. Designed a BI dashboard with automated insights and recommendations for business users.

Skills Used: Python, OpenAI GPT, LangChain, Multi-Agent, Azure OpenAI, Vector DB, Prompt Engineering, Agentic AI, RAG, Semantic Search Roles & Responsibilities: Architected and developed an autonomous business intelligence platform using multi-agent AI architecture. Designed specialized AI agents for data analysis, reporting, and strategic recommendation generation. Implemented autonomous workflows using LangChain and OpenAI GPT models for intelligent data interpretation. Built an automated report generation system capable of producing business insights from structured data. Developed an AI-driven insight discovery system to detect trends, anomalies, and business opportunities. Created a strategic recommendation engine that suggests actionable business decisions. Applied advanced prompt engineering techniques to improve accuracy and contextual understanding. Integrated vector databases for knowledge retrieval and contextual reasoning. Designed a BI dashboard with automated insights and recommendations for business users.

2025 - Present

ML DATA ASSOCIATE

AppenTextClassificationQuestion Answering

Designed and implemented a scalable data labelling pipeline to create high-quality annotated datasets for training supervised machine learning models.

Designed and implemented a scalable data labelling pipeline to create high-quality annotated datasets for training supervised machine learning models.

2025

Intelligent Customer Support Chatbot (Generative AI)

TextComputer Programming Coding

Designed and developed a Generative AI-powered chatbot to provide 24/7 automated customer support for an e-commerce platform. Implemented a Retrieval-Augmented Generation (RAG) architecture to retrieve relevant information from internal documentation and generate accurate responses. The solution improved customer experience and reduced support ticket volume significantly.

Designed and developed a Generative AI-powered chatbot to provide 24/7 automated customer support for an e-commerce platform. Implemented a Retrieval-Augmented Generation (RAG) architecture to retrieve relevant information from internal documentation and generate accurate responses. The solution improved customer experience and reduced support ticket volume significantly.

2024 - 2025

AIML ENGINEER

Computer Code ProgrammingFine Tuning

Developed a machine learning model to predict customer churn, helping businesses identify customers likely to leave and take proactive retention actions. The solution used historical customer behavior data to generate churn predictions and insights for customer retention strategies.

Developed a machine learning model to predict customer churn, helping businesses identify customers likely to leave and take proactive retention actions. The solution used historical customer behavior data to generate churn predictions and insights for customer retention strategies.

2023 - 2023

Education

Work History