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AI/ML Engineer with 4+ years of experience specializing in MLOps lifecycles, Generative AI, and RAG architectures in cloud-native environments (AWS/GCP). Experienced in building high-availability production systems by translating complex data signals into measurable business outcomes. Proficient in end-to-end ML engineering including pipeline orchestration, CI/CD, monitoring, and secure deployments, with a strong focus on integrating cutting-edge ML research into scalable enterprise solutions.…AI/ML Engineer with 4+ years of experience specializing in MLOps lifecycles, Generative AI, and RAG architectures in cloud-native environments (AWS/GCP). Experienced in building high-availability production systems by translating complex data signals into measurable business outcomes. Proficient in end-to-end ML engineering including pipeline orchestration, CI/CD, monitoring, and secure deployments, with a strong focus on integrating cutting-edge ML research into scalable enterprise solutions.

Prakash Reddy Korepu

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AI/ML Engineer with 4+ years of experience specializing in MLOps lifecycles, Generative AI, and RAG architectures in cloud-native environments (AWS/GCP). Experienced in building high-availability production systems by translating complex data signals into measurable business outcomes. Proficient in end-to-end ML engineering including pipeline orchestration, CI/CD, monitoring, and secure deployments, with a strong focus on integrating cutting-edge ML research into scalable enterprise solutions.…AI/ML Engineer with 4+ years of experience specializing in MLOps lifecycles, Generative AI, and RAG architectures in cloud-native environments (AWS/GCP). Experienced in building high-availability production systems by translating complex data signals into measurable business outcomes. Proficient in end-to-end ML engineering including pipeline orchestration, CI/CD, monitoring, and secure deployments, with a strong focus on integrating cutting-edge ML research into scalable enterprise solutions.

Available to hire

AI/ML Engineer with 4+ years of experience specializing in MLOps lifecycles, Generative AI, and RAG architectures in cloud-native environments (AWS/GCP). Experienced in building high-availability production systems by translating complex data signals into measurable business outcomes.

Proficient in end-to-end ML engineering including pipeline orchestration, CI/CD, monitoring, and secure deployments, with a strong focus on integrating cutting-edge ML research into scalable enterprise solutions.

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Work Experience

AI/ML Engineer at Fidelity

August 1, 2024 - Present

Constructed scalable MLOps pipelines using Amazon SageMaker to deploy models 40% faster than prior manual workflows. Implemented generative AI workflows with LangChain and Hugging Face, improving automated business-critical task efficiency by 25%. Built RAG architectures over large enterprise datasets, reducing retrieval latency by 50%. Orchestrated end-to-end MLOps with MLflow and Kubernetes, achieving 99.99% uptime and reducing model deployment time by 30% via automated CI/CD. Enforced security and compliance using AWS IAM and Model Monitor for regulatory adherence. Led cross-functional enterprise AI integrations, improving team operational throughput by 15% YoY, and mentored 5+ junior engineers in secure, high-concurrency AI systems.

Machine Learning Engineer at Hexaware Technologies

January 1, 2020 - July 1, 2022

Developed predictive models using GCP Vertex AI and BigQuery, achieving 95% accuracy on 5TB+ enterprise datasets. Improved production-ready delivery by 30% using Vertex AI Pipelines orchestration. Optimized data ingestion by improving Pandas and SQL pipelines, reducing overhead by 20%. Integrated models into production RESTful APIs supporting 50,000+ daily live requests. Standardized deployments with Docker, reducing configuration issues by 35%. Improved predictive accuracy by 10% through iterative hyperparameter tuning and automated feature engineering that enhanced data quality and system reliability by 15%. Collaborated with stakeholders to translate requirements into scalable project roadmaps.