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Hello! I am an AI/ML Engineer with 5+ years of experience delivering enterprise AI and intelligent automation solutions across financial services and digital platforms. I thrive on turning complex data into scalable, production-ready systems and enjoy collaborating with product teams to drive measurable business impact. In my work at Accenture and Adobe, I designed models, built real-time inference pipelines, and implemented MLOps practices to boost deployment speed, reliability, and governance. I am passionate about scalable ML architecture, Generative AI, and responsible AI deployment, always aiming to reduce latency, improve accuracy, and empower decision-makers.…Hello! I am an AI/ML Engineer with 5+ years of experience delivering enterprise AI and intelligent automation solutions across financial services and digital platforms. I thrive on turning complex data into scalable, production-ready systems and enjoy collaborating with product teams to drive measurable business impact. In my work at Accenture and Adobe, I designed models, built real-time inference pipelines, and implemented MLOps practices to boost deployment speed, reliability, and governance. I am passionate about scalable ML architecture, Generative AI, and responsible AI deployment, always aiming to reduce latency, improve accuracy, and empower decision-makers.

Saran Kumar Durgam

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Hello! I am an AI/ML Engineer with 5+ years of experience delivering enterprise AI and intelligent automation solutions across financial services and digital platforms. I thrive on turning complex data into scalable, production-ready systems and enjoy collaborating with product teams to drive measurable business impact. In my work at Accenture and Adobe, I designed models, built real-time inference pipelines, and implemented MLOps practices to boost deployment speed, reliability, and governance. I am passionate about scalable ML architecture, Generative AI, and responsible AI deployment, always aiming to reduce latency, improve accuracy, and empower decision-makers.…Hello! I am an AI/ML Engineer with 5+ years of experience delivering enterprise AI and intelligent automation solutions across financial services and digital platforms. I thrive on turning complex data into scalable, production-ready systems and enjoy collaborating with product teams to drive measurable business impact. In my work at Accenture and Adobe, I designed models, built real-time inference pipelines, and implemented MLOps practices to boost deployment speed, reliability, and governance. I am passionate about scalable ML architecture, Generative AI, and responsible AI deployment, always aiming to reduce latency, improve accuracy, and empower decision-makers.

Available to hire

Hello! I am an AI/ML Engineer with 5+ years of experience delivering enterprise AI and intelligent automation solutions across financial services and digital platforms. I thrive on turning complex data into scalable, production-ready systems and enjoy collaborating with product teams to drive measurable business impact.

In my work at Accenture and Adobe, I designed models, built real-time inference pipelines, and implemented MLOps practices to boost deployment speed, reliability, and governance. I am passionate about scalable ML architecture, Generative AI, and responsible AI deployment, always aiming to reduce latency, improve accuracy, and empower decision-makers.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at Accenture

November 1, 2024 - Present

Led the architecture and deployment of end-to-end machine learning solutions for enterprise clients in financial services and retail, driving AI initiatives that delivered $150M+ in operational efficiencies and revenue optimization. Designed and optimized ML models (XGBoost, Random Forest, Deep Neural Networks, Transformer architectures) on structured and unstructured data exceeding 20M records, boosting predictive accuracy by 22–28% across classification, forecasting, and risk modeling use cases. Built scalable data ingestion and feature engineering pipelines using Python and SQL with distributed processing, reducing data prep time by 35% and improving data quality and reproducibility. Implemented NLP-driven automation for large-scale document processing, entity recognition, and sentiment analysis, increasing operational efficiency by 40% and cutting manual review cycles. Deployed real-time inference APIs and microservices handling 1M+ daily predictions, lowering serving latency by

Machine Learning Engineer at Adobe

January 1, 2019 - June 1, 2023

Designed and deployed scalable ML models powering personalization and content optimization for 5M+ global users, improving recommendation accuracy by 21% and increasing user engagement. Built supervised and deep learning models (Gradient Boosting, XGBoost, Neural Networks, Transformer-based architectures) on datasets exceeding 15M+ user interaction records, improving prediction precision and recall by 20%+. Developed robust feature engineering pipelines integrating behavioral, transactional, and content metadata (150+ engineered features), enhancing model performance and reducing noise in large-scale datasets. Implemented NLP-based solutions for document classification, tagging, and sentiment analysis, increasing automated content processing efficiency by 38%. Designed real-time inference services supporting 2M+ daily predictions, optimizing latency by 18% through model compression and efficient serving mechanisms. Led hyperparameter tuning, cross-validation, and model benchmarking pro