Azure ML Platform Engineer - MLOps for LLM Infra

Alloy Enterprises; Dallas (TX); On-site; USD 85,000 - 107,000; Full time

Job summary

Johnson Controls International plc. seeks a Machine Learning / Platform Engineer to join the AI and Data Platform team.

You will build scalable ML/LLM pipelines on Azure with DevOps tooling, manage Terraform-based infrastructure, and operationalize LLMs with strong security and governance. You’ll bridge ML, cloud engineering, and platforms to deliver production-grade AI features, focusing on Azure-native MLOps components, AKS, and automated deployments.

Qualifications

• Bachelor’s or Master’s in Computer Science, Engineering, or a related field.
• 5+ years of experience in ML engineering, MLOps, or platform engineering.
• Strong experience deploying machine learning models on Azure using Azure ML and Azure DevOps.
• Proven experience managing infrastructure as code with Terraform in production environments.

Responsibilities

• Build 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 with a focus on automation, security, and scalability.
• Develop and manage infrastructure as code using Terraform, provisioning AKS, Azure resources, storage, and networking.
• Implement robust model lifecycle management with Azure-native MLOps components.
• Design serving environments for LLM inference using AKS and App Services.
• Build and manage RAG pipelines using vector databases and orchestration tools.
• Collaborate with Data Scientists, Cloud Engineers, and Product Teams to deliver production-ready AI features.

Skills

Python

Azure

Azure ML

Azure DevOps

Terraform

CI/CD

LangChain

Transformers

PyTorch

Education

Bachelor’s or Master’s in Computer Science, Engineering, or related field

Tools

Docker

Kubernetes

Azure ML Pipelines

Terraform Scripts

Job description

Johnson Controls International plc. seeks a Machine Learning / Platform Engineer to join the AI and Data Platform team.

You will build scalable ML/LLM pipelines on Azure with DevOps tooling, manage Terraform-based infrastructure, and operationalize LLMs with strong security and governance. You’ll bridge ML, cloud engineering, and platforms to deliver production-grade AI features, focusing on Azure-native MLOps components, AKS, and automated deployments.