Venkata Krishna Ullam
Ai Ml Engineer @Cigna Healthcare
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WORK HISTORY
Ai Ml Engineer @Cigna Healthcare
Developed machine learning models using PyTorch and Transformers to support clinical risk prediction and claims-related use cases, enabling data driven healthcare decision-making. • Integrated Large Language Models with LangChain and Hugging Face to build retrieval-augmented workflows for querying structured and unstructured medical data, improving information accessibility for stakeholders. • Engineered distributed data processing and training pipelines using Spark and AWS to handle large-scale healthcare datasets, supporting efficient model training and scalability. • Deployed containerized model inference services using FastAPI and Docker on cloud infrastructure, enabling low-latency and scalable access to production-grade ML models. • Implemented MLOps workflows using MLflow and CI/CD pipelines, reducing deployment errors by 20% and improving model versioning and monitoring in production environments. • Optimized model performance using quantization, caching, and GPU tuning techniques, reducing inference latency by 25% while maintaining prediction accuracy for real-time applications.
EDUCATION
KL University
Bachelor of Technology, Electrical, Electronics and Communications Engineering
Pace University
Master of Science, Data Science
ABOUT VENKATA KRISHNA ULLAM
AI/ML Engineer with 5+ years of experience building scalable machine learning and Generative AI systems across enterprise and healthcare environments. Skilled in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), NLP, and end-to-end ML system development using PyTorch, Transformers, AWS, Spark, Docker, and Kubernetes.Experienced in developing distributed data pipelines, deploying low-latency inference APIs with FastAPI, and implementing MLOps practices with MLflow and CI/CD to deliver production-ready AI solutions. Passionate about building intelligent systems that solve real-world problems and create business impact.Open to opportunities in Senior AI/ML Engineer, LLM Engineer, and Machine Learning Engineer roles.
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