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I am Sumedh Anumala, an Artificial Intelligence and Machine Learning Engineer with 3+ years of experience architecting enterprise-grade Generative AI pipelines and scalable MLOps infrastructures. I specialize in deploying high-throughput, low-latency LLMs and orchestrating complex agentic workflows that drive sub-second inferences and multi-million-dollar operational efficiencies. I partner with cross-functional teams to deliver end-to-end AI services, from data ingestion and feature engineering to model deployment and observability. I enjoy building robust, observable systems with tools like LangSmith, W&B, and MLflow, and I continually explore state-of-the-art techniques in RAG, retrieval, and generative AI to unlock business impact.…I am Sumedh Anumala, an Artificial Intelligence and Machine Learning Engineer with 3+ years of experience architecting enterprise-grade Generative AI pipelines and scalable MLOps infrastructures. I specialize in deploying high-throughput, low-latency LLMs and orchestrating complex agentic workflows that drive sub-second inferences and multi-million-dollar operational efficiencies. I partner with cross-functional teams to deliver end-to-end AI services, from data ingestion and feature engineering to model deployment and observability. I enjoy building robust, observable systems with tools like LangSmith, W&B, and MLflow, and I continually explore state-of-the-art techniques in RAG, retrieval, and generative AI to unlock business impact.

Sumedh Anumala

AI Engineer, Data Scientist, Full Stack Developer, +2

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I am Sumedh Anumala, an Artificial Intelligence and Machine Learning Engineer with 3+ years of experience architecting enterprise-grade Generative AI pipelines and scalable MLOps infrastructures. I specialize in deploying high-throughput, low-latency LLMs and orchestrating complex agentic workflows that drive sub-second inferences and multi-million-dollar operational efficiencies. I partner with cross-functional teams to deliver end-to-end AI services, from data ingestion and feature engineering to model deployment and observability. I enjoy building robust, observable systems with tools like LangSmith, W&B, and MLflow, and I continually explore state-of-the-art techniques in RAG, retrieval, and generative AI to unlock business impact.…I am Sumedh Anumala, an Artificial Intelligence and Machine Learning Engineer with 3+ years of experience architecting enterprise-grade Generative AI pipelines and scalable MLOps infrastructures. I specialize in deploying high-throughput, low-latency LLMs and orchestrating complex agentic workflows that drive sub-second inferences and multi-million-dollar operational efficiencies. I partner with cross-functional teams to deliver end-to-end AI services, from data ingestion and feature engineering to model deployment and observability. I enjoy building robust, observable systems with tools like LangSmith, W&B, and MLflow, and I continually explore state-of-the-art techniques in RAG, retrieval, and generative AI to unlock business impact.

Available to hire

I am Sumedh Anumala, an Artificial Intelligence and Machine Learning Engineer with 3+ years of experience architecting enterprise-grade Generative AI pipelines and scalable MLOps infrastructures. I specialize in deploying high-throughput, low-latency LLMs and orchestrating complex agentic workflows that drive sub-second inferences and multi-million-dollar operational efficiencies. I partner with cross-functional teams to deliver end-to-end AI services, from data ingestion and feature engineering to model deployment and observability. I enjoy building robust, observable systems with tools like LangSmith, W&B, and MLflow, and I continually explore state-of-the-art techniques in RAG, retrieval, and generative AI to unlock business impact.

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Advanced

Work Experience

Artificial Intelligence (AI) Engineer at PNC Bank

January 1, 2025 - Present

Architected a multi-agent compliance review system utilizing CrewAI and LangGraph, automating the parsing of 2TB+ of unstructured regulatory documents and reducing manual audit cycle times by 40%. Engineered a Graph Retrieval-Augmented Generation (GraphRAG) architecture plumbing Neo4j and LlamaIndex to improve complex semantic query retrieval accuracy by 35% for risk analysts. Deployed heavily quantized (AWQ) Llama-3 models via vLLM and TensorRT-LLM on AWS GPU clusters, driving a 3x increase in inference throughput while reducing quarterly compute infrastructure costs by $150K. Integrated LangSmith and Ragas into the CI/CD pipeline for real-time LLM observability with strict 99.9% factual accuracy in client-facing outputs. Implemented real-time transaction telemetry using Apache Kafka into a PyTorch-based deep learning anomaly detector, slashing fraud detection latency to sub-50ms during peak volumes. Conducted QLoRA fine-tuning on banking datasets, enhancing domain-specific financial

Machine Learning Engineer at Sage SoftTech

June 1, 2021 - August 1, 2023

Developed CNNs in PyTorch for automated document OCR pipeline processing 5M+ scans with 96% text extraction accuracy. Deployed BERT-based transformers for enterprise sentiment analysis and improved customer support ticket routing by 25%. Architected ETL pipelines with Apache Spark and Databricks to cleanse and transform 10TB of data, accelerating feature engineering by 50%. Built an XGBoost-based churn model with feature engineering and hyperparameter tuning, boosting ROC-AUC to 0.89 and preserving ~$77K in annual revenue. Integrated dense vector embeddings into Qdrant and Milvus to enable sub-100ms semantic search. Standardized ML lifecycle with MLflow and Weights & Biases, accelerating cross-team iteration by 30%. Automated end-to-end retraining pipelines with Apache Airflow and data drift detection to maintain accuracy.