Vanguri Mallaiah

• Engineered and deployed Generative AI–driven solutions to enhance banking workflows, ensuring secure, compliant, and well-tested code across financial applications.
• Developed clean, modular, and dynamic AI components, leveraging Python and large language model (LLM) frameworks to meet diverse banking use cases such as customer service automation, fraud detection support, and risk analysis.
• Implemented agile-based, testable AI models and micro services, ensuring regulatory compliance, high-quality deliverables, and seamless integration with Wells Fargo’s enterprise data platforms.
• Coordinated team resources and sprint priorities, aligning Generative AI development goals with banking regulatory timelines and cross-functional stakeholder expectations.
• Partnered with quality assurance teams to validate AI outputs, design test cases for bias/accuracy checks, and investigate issues to strengthen model reliability and audit ability.
• Generative AI – Banking Domain Wells Fargo

Identified and applied suitable ML technologies and frameworks Tensor Flow, to develop healthcare solutions tailored to local community needs such as disease prediction, patient monitoring, and health record analysis.

• Collaborated with cross-disciplinary teams medical experts, data engineers, to design systems that address real-world healthcare challenges and client requirements.
• Developed and enforced quality assurance procedures to minimize data processing and coding errors in ML models, ensuring reliable and safe outputs for clinical decision-making.
• Prepared comprehensive documentation of ML workflows, data standards, and compliance procedures in alignment with organizational policies and healthcare regulatory requirements, HIPAA.
• Deployed and validated functional ML solutions by designing, adopting, and executing test plans that ensured the accuracy, fairness, and integrity of predictive healthcare systems.
• Healthcare Project – Machine Learning
• Analyzed system performance metrics to identify bottlenecks and optimize application responsiveness.

• Identified and applied advanced technology approaches GPU acceleration, deep learning frameworks to design and develop high-performance AI/ML solutions adaptable to diverse project needs.
• Collaborated with cross-functional teams research scientists, data engineers, and software developers to architect systems optimized for client requirements and large-scale computational workloads.
• Developed and implemented robust quality assurance workflows to minimize coding errors, ensure model reproducibility, and maintain high performance on GPU-accelerated platforms.
• Created and maintained technical documentation of standards, procedures, and ML pipelines in alignment with organizational best practices and client deliverables.
• NVIDIA Project – AI/ML System
• Implemented automated testing strategies to improve code quality and reduce deployment errors.
• Contributed to architectural design decisions, ensuring alignment with business objectives and technology standards.
• Automated repetitive tasks using Python scripts, increasing efficiency within the team''s workflow processes.

• Developed and maintained scalable web applications using JavaScript frameworks.
• Collaborated with cross-functional teams to define project requirements and deliver effective solutions.
• Implemented automated testing procedures to improve code quality and reduce deployment errors.
• Optimized application performance through code reviews and debugging techniques.