snehabhalerao AI/ML Engineer Portfolio

Transforming Development With Innovative Frameworks And Architectures For Cutting-Edge Agentic AI and NLP systems.

Personal work that tells my story

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AI Engineer - NLP Specialization

Projects

Screenshot of a chatbot interface demonstrating natural language understanding.

StratoVector.ai

Visualization of sentiment analysis results on social media data.

Code snippet showing transformer model fine-tuning for text classification.

Dashboard displaying real-time AI model performance metrics.

ML DL Projects

Analyzing data and building models using ML and DL

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Modular Retrieval-Augmented Generation Framework

Experience Highlights

Pioneering Work in Agentic AI Architectures and Scalable AI Engineering

Built advanced agentic AI frameworks, including a multi-agent workflow engine and a memory-coordinated architecture enabling truly asynchronous, coordinated agent behavior.
Engineered high-performance synthetic data systems, creating a platform capable of generating ~10GB of domain-accurate data in minutes across retail, finance, and travel domains.
Developed unified AI interoperability tooling, including an SDK that seamlessly integrates A2A and MCP protocols within a single framework for extensible agent–tool communication.
Created next-generation AI developer SDKs—StratoVector.ai for automated RAG pipeline construction and TuneLLM.ai for accessible, advanced LLM fine-tuning without deep AI/ML specialization.

Passionate about crafting smarter AI systems.

Work

AI Engineer

Adobe

Jan 2024 - Present

Engineered custom ML models and Generative AI applications, designing full-stack architectures to support complex, production-grade AI systems. Led development of a Python-based agentic AI framework, fine-tuned safety-aligned LLMs, and built scalable components including a high-throughput synthetic data generator for domain-specific datasets.

AI/ML Engineer

Deloitte India

Apr 2022 - Jan 2024

Designed AI/ML solution architectures and built NLP systems for sentence structure detection, grammar correction, text scoring, readability assessment, classification, and topic modeling, including fine-tuned LLMs for audit-focused use cases.