Jeetsingh Chauhan

I specialize in deploying robust, scalable compute infrastructure in Microsoft Azure to support AI and Machine Learning workloads—primarily using Infrastructure as Code (IaC) tools such as Terraform. In recent fintech projects, I’ve been responsible for: 🔹 Designing and provisioning Azure compute resources (e.g., VMs, Azure Kubernetes Service (AKS), Azure ML Compute Instances) to support AI/ML model training, inference, and API deployments. 🔹 Automating infrastructure deployment using Terraform to ensure consistency, scalability, and version-controlled environments across development, testing, and production. 🔹 Creating reusable Terraform modules for: Azure Machine Learning Workspaces GPU-enabled Virtual Machines for model training Containerized inference endpoints (via Azure Container Instances or AKS) Secure storage and networking (Azure Blob Storage, Key Vault, VNet) 🔹 Deploying GPT and custom ML models into production environments for use cases such as financial document analysis, risk prediction, and intelligent automation. 🔹 Integrating Azure DevOps pipelines with Terraform for seamless CI/CD of AI infrastructure components, with built-in compliance, monitoring, and logging. 🔹 Ensuring enterprise-grade governance including RBAC, network isolation, Key Vault-based secret management, and Azure Policy enforcement to meet strict fintech regulatory requirements. My work bridges the gap between data science and operations—empowering teams to move ML models from research to production swiftly and securely using modern cloud-native infrastructure practices.

Over the past few years, I’ve been actively involved in: 🔹 Researching and developing machine learning models for data prediction and trend analysis—working on use cases such as customer behavior forecasting, anomaly detection, and business KPI predictions. 🔹 Participating in end-to-end ML workflows including data collection, cleaning, model training, validation, and testing. 🔹 Hands-on work with OpenAI technologies to explore NLP capabilities and automation use cases. 🔹 Integrating Microsoft Copilot into business processes to enhance productivity, automate repetitive tasks, and provide intelligent insights. 🔹 Operating in Agile environments, collaborating cross-functionally to deliver iterative value through fast prototyping and continuous feedback. I’m continuously exploring AI-driven solutions to solve real-world problems while staying committed to learning and evolving in this fast-paced digital landscape.