Venkata Pavana Srichandana Tokala
Genai Ml Engineer @Bank of America
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WORK HISTORY
Genai Ml Engineer @Bank of America
Kent, OH, US
Building and optimizing LLM-powered applications for enterprise use cases such as classification, summarization, semantic retrieval, and conversational workflows used by internal teams.Designed RAG pipelines using LangChain, FAISS, and Azure Cognitive Search, significantly improving retrieval quality and reducing irrelevant responses in downstream LLM outputs.Developed AI copilots and multi-turn assistants using Microsoft Copilot Studio, integrating tool calling and memory to automate repetitive business processes and improve user efficiency.Built embedding-based semantic search systems using OpenAI, Cohere, Azure Embeddings, FAISS, and Qdrant to enable faster and more accurate information retrieval across large document sets.Deployed fine-tuned transformer models and GenAI services using FastAPI, Docker, and AKS, focusing on scalability, reliability, and smooth production rollouts.Set up MLOps workflows with Azure ML, MLflow, DVC, and GitHub Actions to support model versioning, retraining, monitoring, and handling model drift in production environments.
ABOUT VENKATA PAVANA SRICHANDANA TOKALA
I’m a Generative AI and Machine Learning Engineer with 3.5+ years of experience building production-ready AI systems across GenAI, NLP, forecasting, and applied ML. I’ve developed solutions such as LLM copilots, RAG pipelines, semantic search systems, forecasting models, and scalable ML APIs that help organizations improve decision-making and efficiency.My work focuses on the end-to-end AI lifecycle—from problem understanding and model design to deployment. I’m particularly interested in RAG, agentic workflows, prompt optimization, and production-grade MLOps using tools like Python, PyTorch, LangChain, FastAPI, Azure OpenAI, FAISS, Qdrant, MLflow, Docker, and Kubernetes.I’m happy to connect about Generative AI, ML, or applied AI projects: c••••••••@gmail.com
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