Role overview
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.
What we're looking for
- Experience with LLMOps, prompt orchestration frameworks (LangChain, Semantic Kernel), and open-weight model deployment.
- Exposure to smart buildings, IoT, or edge-AI deployments.
- Understanding of governance, privacy, and compliance concerns in enterprise GenAI use cases.
- Certification in Azure (e.g., Azure Solutions Architect, Azure AI Engineer, Terraform Associate) is a plus.
HIRING SALARY RANGE: $85,000 - 107,000 (Salary to be determined by the education, experience, knowledge, skills, and abilities of the applicant, internal equity, location and alignment with market data.) This position includes a competitive benefits package. For details, please visit the About Us tab on the Johnson Controls Careers site at https://jobs.johnsoncontrols.com/about-us