Ai/ML Engineer

About this role

Johnson Controls International (JCI) is looking for a Machine Learning / Platform Engineer to join our growing AI and Data Platform team. This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building secure, scalable, and automated infrastructure on Azure using Terraform and Azure DevOps.

You’ll work at the intersection of ML, DevOps, and cloud engineering—building the foundation that supports real-time LLM inference, retraining, orchestration, and integration across JCI’s product and operations landscape.

How you will do it

ML Platform Engineering & MLOps (Azure-Focused)

• Build and manage end-to-end ML/LLM pipelines on **Azure ML** using **Azure DevOps** for CI/CD, testing, and release automation.
• Operationalize LLMs and generative AI solutions (e.g., GPT, LLaMA, Claude) with a focus on automation, security, and scalability.
• Develop and manage infrastructure as code using **Terraform**, including provisioning compute clusters (e.g., Azure Kubernetes Service, Azure Machine Learning compute), storage, and networking.
• Implement robust model lifecycle management (versioning, monitoring, drift detection) with Azure-native MLOps components.

Infrastructure & Cloud Architecture

• Design highly available and performant serving environments for LLM inference using **Azure Kubernetes Service (AKS)** and **Azure Functions** or **App Services**.
• Build and manage RAG pipelines using vector databases (e.g., Azure Cognitive Search, Redis, FAISS) and orchestrate with tools like **LangChain** or **Semantic Kernel**.
• Ensure security, logging, role-based access control (RBAC), and audit trails are implemented consistently across environments.

Automation & CI/CD Pipelines

• Build reusable **Azure DevOps pipelines** for deploying ML assets (data pre-processing, model training, evaluation, and inference services).
• Use Terraform to automate provisioning of Azure resources, ensuring consistent and compliant environments...