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I am an AI/ML Engineer with 4+ years of experience designing and deploying scalable, production-ready AI solutions in financial services. I specialize in building end-to-end ML pipelines, data engineering, fraud detection, personalization systems, and real-time analytics using Python, PySpark, SQL, and cloud-native architectures.\n\nI am proficient in NLP, Generative AI, transformer-based models, MLOps, and regulatory-compliant model monitoring. I enjoy translating complex business problems into AI-driven insights, optimizing model performance, and delivering measurable impact across global production environments.…I am an AI/ML Engineer with 4+ years of experience designing and deploying scalable, production-ready AI solutions in financial services. I specialize in building end-to-end ML pipelines, data engineering, fraud detection, personalization systems, and real-time analytics using Python, PySpark, SQL, and cloud-native architectures.\n\nI am proficient in NLP, Generative AI, transformer-based models, MLOps, and regulatory-compliant model monitoring. I enjoy translating complex business problems into AI-driven insights, optimizing model performance, and delivering measurable impact across global production environments.

Srinath Nallanagula

AI Engineer, Data Scientist, Full Stack Developer, +4

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I am an AI/ML Engineer with 4+ years of experience designing and deploying scalable, production-ready AI solutions in financial services. I specialize in building end-to-end ML pipelines, data engineering, fraud detection, personalization systems, and real-time analytics using Python, PySpark, SQL, and cloud-native architectures.\n\nI am proficient in NLP, Generative AI, transformer-based models, MLOps, and regulatory-compliant model monitoring. I enjoy translating complex business problems into AI-driven insights, optimizing model performance, and delivering measurable impact across global production environments.…I am an AI/ML Engineer with 4+ years of experience designing and deploying scalable, production-ready AI solutions in financial services. I specialize in building end-to-end ML pipelines, data engineering, fraud detection, personalization systems, and real-time analytics using Python, PySpark, SQL, and cloud-native architectures.\n\nI am proficient in NLP, Generative AI, transformer-based models, MLOps, and regulatory-compliant model monitoring. I enjoy translating complex business problems into AI-driven insights, optimizing model performance, and delivering measurable impact across global production environments.

Available to hire

I am an AI/ML Engineer with 4+ years of experience designing and deploying scalable, production-ready AI solutions in financial services. I specialize in building end-to-end ML pipelines, data engineering, fraud detection, personalization systems, and real-time analytics using Python, PySpark, SQL, and cloud-native architectures.\n\nI am proficient in NLP, Generative AI, transformer-based models, MLOps, and regulatory-compliant model monitoring. I enjoy translating complex business problems into AI-driven insights, optimizing model performance, and delivering measurable impact across global production environments.

Skills

Experience Level

Expert

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Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at Marqeta

February 1, 2025 - Present

Led the development of an AI-driven Fraud Detection and Risk Analytics platform processing millions of transactions daily. Achieved a 35% reduction in potential fraud exposure, improved risk response speed, and ensured PCI-DSS, SOC 2, and SOX compliance. Built end-to-end data ingestion and transformation pipelines with Python, SQLAlchemy, and Pydantic, achieving 99.5% schema validation accuracy. Engineered transaction-level NLP features and fine-tuned Longformer/FinBERT with domain adaptation (LoRA/PEFT) to boost performance while cutting compute costs by ~40%. Implemented real-time RAG pipelines with LangChain, FAISS, and AWS Lambda for rapid historical lookups, increasing query accuracy by 30% and reducing investigation time by 35%. Established scalable ML monitoring and retraining frameworks for auditable, production-grade deployments across Marqeta's global payments ecosystem.

AI/ML Engineer at Broadridge Financial Solutions, Inc.

June 1, 2020 - December 1, 2023

Designed the Smart Financial Personalization Engine using Python, SQL, and Spark. Built scalable ETL and feature engineering pipelines with PySpark and Airflow, integrating data from MySQL, Hive, and real-time streams. Developed models (XGBoost, Transformer encoders) to predict churn, anomalies, and fraud, achieving high precision and robustness. Applied hyperparameter tuning, cross-validation, and SHAP explainability to ensure transparency and regulatory compliance. Deployed containerized ML microservices with Docker, Kubernetes, gRPC, Kafka, and Redis, achieving <100ms latency and 99.9% uptime. Collaborated with Product/Risk/UX teams to run A/B tests, increasing conversions and reducing false positives.

AI/ML Engineer at Marqeta

February 1, 2015 - Present

Developed an AI-driven Fraud Detection and Risk Analytics platform analyzing millions of payment transactions daily, detecting anomalies and suspicious patterns, reducing potential fraud exposure by 35%, and accelerating risk response while ensuring PCI-DSS, SOC 2, and SOX compliance. Built end-to-end data ingestion and transformation pipelines using Python, SQLAlchemy, and Pydantic; structured data in PostgreSQL for auditability and regulatory compliance at scale. Engineered transaction-level NLP features and RAG pipelines with LangChain and AWS Lambda; implemented automated retraining and monitoring for regulatory compliance.