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I am an AI/ML Engineer passionate about building reliable, scalable AI systems that solve real business problems. Over the past 4+ years, I have engineered production ML and generative AI solutions, from fraud detection to real-time decisioning, across enterprise environments. I enjoy bridging ML research with practical engineering—designing end-to-end data pipelines, model evaluation, and cloud deployments on AWS and GCP. I thrive in collaborative teams and have led cross-functional groups to accelerate ML initiatives while maintaining security and cost discipline.…I am an AI/ML Engineer passionate about building reliable, scalable AI systems that solve real business problems. Over the past 4+ years, I have engineered production ML and generative AI solutions, from fraud detection to real-time decisioning, across enterprise environments. I enjoy bridging ML research with practical engineering—designing end-to-end data pipelines, model evaluation, and cloud deployments on AWS and GCP. I thrive in collaborative teams and have led cross-functional groups to accelerate ML initiatives while maintaining security and cost discipline.

Girish Krishna Kurra

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I am an AI/ML Engineer passionate about building reliable, scalable AI systems that solve real business problems. Over the past 4+ years, I have engineered production ML and generative AI solutions, from fraud detection to real-time decisioning, across enterprise environments. I enjoy bridging ML research with practical engineering—designing end-to-end data pipelines, model evaluation, and cloud deployments on AWS and GCP. I thrive in collaborative teams and have led cross-functional groups to accelerate ML initiatives while maintaining security and cost discipline.…I am an AI/ML Engineer passionate about building reliable, scalable AI systems that solve real business problems. Over the past 4+ years, I have engineered production ML and generative AI solutions, from fraud detection to real-time decisioning, across enterprise environments. I enjoy bridging ML research with practical engineering—designing end-to-end data pipelines, model evaluation, and cloud deployments on AWS and GCP. I thrive in collaborative teams and have led cross-functional groups to accelerate ML initiatives while maintaining security and cost discipline.

Available to hire

I am an AI/ML Engineer passionate about building reliable, scalable AI systems that solve real business problems. Over the past 4+ years, I have engineered production ML and generative AI solutions, from fraud detection to real-time decisioning, across enterprise environments.

I enjoy bridging ML research with practical engineering—designing end-to-end data pipelines, model evaluation, and cloud deployments on AWS and GCP. I thrive in collaborative teams and have led cross-functional groups to accelerate ML initiatives while maintaining security and cost discipline.

Skills

Experience Level

Expert

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Intermediate

Work Experience

AI/ML Engineer at Scale AI

January 1, 2025 - Present

Led development of an LLM orchestration layer routing requests across OpenAI, Claude, Llama, and fine-tuned models based on latency, cost, and compliance constraints for enterprise workloads. Built RAG systems using FAISS, Pinecone, and pgvector and created end-to-end ingestion pipelines to convert PDFs, tables, logs, and audio into structured formats for LLM and agent workflows. Improved query latency by 35% through embedding caching, request batching, and optimized vector search for high-traffic AI workloads. Implemented real-time inference services via REST and gRPC with token streaming and autoscaling on Kubernetes to support multi-tenant AI apps. Reduced LLM operational costs by 25% through routing strategies, selective retrieval, and fallback mechanisms during multi-step agent execution. Collaborated with infrastructure and security teams to deploy GPU-backed inference on AWS and GCP with private networking and encryption. Built evaluation and reliability frameworks with golden d

Full Stack Developer at Fidelity Investments

January 1, 2025 - Present

Developed secure trading applications using Python and React.js, supporting 10,000+ daily interactions and transactions. Created backend services and API integrations for enterprise financial platforms, ensuring PCI-compliant data handling and reducing failed transactions. Optimized database queries and relational models across PostgreSQL and MySQL, improving dashboard load times and reporting accuracy for compliance monitoring. Built Power BI and Tableau dashboards to track operational KPIs and investment processing metrics, enabling faster, data-driven decisions. Led cross-functional collaboration with product managers and QA to deliver high-quality features on schedule.

Machine Learning Engineer at Mastercard

June 1, 2020 - July 1, 2023

Built and deployed an XGBoost-based fraud detection system for real-time transaction scoring, with SHAP-based explanations to aid compliance and risk teams. Developed ML pipelines for time-series anomaly detection, achieving cost reductions of approximately $150K annually through early identification of unusual patterns. Implemented model tuning and evaluation workflows using Decision Trees and Random Forests, cutting iteration time by 50% and accelerating fraud experimentation. Created internal Python libraries to standardize model training, feature engineering, evaluation, and deployment, boosting deployment efficiency by 400%. Constructed data pipelines to convert structured and unstructured transaction data into ML-ready features, enabling multiple downstream teams. Designed AWS-based monitoring and reporting systems that reduce manual monitoring by 85% and save about $75K annually. Implemented NLP-driven retrieval workflows over internal docs to improve accessibility to operationa

Full Stack Developer at Mastercard

June 1, 2020 - July 1, 2023

Developed secure transactional applications using Python and React.js, supporting 40,000+ daily financial transactions and improving reconciliation efficiency across domestic and international payment systems. Created backend services and API integrations for enterprise financial platforms using Python, ensuring PCI-compliant data handling and reducing failed transactions by 12,000 monthly across MySQL and Oracle databases. Optimized database queries and relational models across PostgreSQL and MySQL, improving dashboard load times by 35% and enhancing reporting accuracy for compliance monitoring. Built Power BI and Tableau dashboards to track operational KPIs, investment processing metrics, and predictive trends, reducing issue resolution time by 20% and improving data-driven decision-making. Collaborated with Agile/Scrum teams, mentoring junior developers and fostering a culture of quality and collaboration across engineering teams.