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Azure Ml Engineer Jobs in Wisconsin (NOW HIRING)

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with AWS, Azure, or GCP. * Strong knowledge of Docker and Kubernetes. * Experience with ...

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Azure Ml Engineer information

What is the difference between Azure Ml Engineer vs Data Scientist?

AspectAzure Ml EngineerData Scientist
Required CredentialsAzure certifications, programming skills, machine learning knowledgeStatistics, programming, data analysis, often with advanced degrees
Work EnvironmentCloud platforms, Azure services, deployment pipelinesData analysis, modeling, research environments, often using Python/R
Employer & Industry UsageTech companies, enterprises leveraging Azure cloudResearch institutions, tech firms, finance, healthcare

Azure Ml Engineers focus on deploying and managing machine learning models within Azure cloud environments, emphasizing cloud infrastructure and deployment. Data Scientists primarily analyze data, develop models, and generate insights, often working in research or analytical settings. While both roles require strong programming and ML knowledge, Azure Ml Engineers are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and model development.

Are Azure ML engineers still in demand?

Azure ML engineers are currently in high demand due to the growing adoption of cloud-based machine learning solutions and the need for expertise in Azure services, data modeling, and deployment. Organizations seek professionals with skills in Azure Machine Learning Studio, Python, and related tools to develop and manage AI models efficiently.

What is the salary of an Azure ML engineer?

The salary of an Azure ML engineer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and certifications. Senior roles or those in high-demand areas may offer higher compensation, especially for professionals with strong skills in machine learning, cloud platforms, and data engineering.

What cities in Wisconsin are hiring for Azure Ml Engineer jobs?

Cities in Wisconsin with the most Azure Ml Engineer job openings:

Ai/ML Engineer

Milwaukee, WI • On-site

$85K - $107K/yr

Other

Posted 8 days ago


Key responsibilities

  • Build and manage end‑to‑end ML/LLM pipelines on Azure using Azure DevOps for CI/CD, testing, and release automation.

  • Operationalize LLMs and generative AI solutions with a focus on automation, security, and scalability.

  • Design and manage infrastructure as code using Terraform, including provisioning compute clusters, storage, and networking.


Job description

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.

ResponsibilitiesML 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 (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
  • Design highly available and performant serving environments for LLM inference using Azure Kubernetes Service and Azure Functions or App Services.
  • Build and manage Retrieval Augmented Generation pipelines using vector databases (Azure Cognitive Search, Redis, FAISS) and orchestrate with tools like LangChain or Semantic Kernel.
  • Ensure security, logging, role‑based access control, 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 for data science and engineering teams.
  • Integrate automated testing, linting, monitoring, and rollback mechanisms into the ML deployment pipeline.
Collaboration & Enablement
  • Work closely with Data Scientists, Cloud Engineers, and Product Teams to deliver production‑ready AI features.
  • Contribute to solution architecture for real‑time and batch AI use cases, including conversational AI, enterprise search, and summarization tools powered by LLMs.
  • Provide technical guidance on cost optimization, scalability patterns, and high‑availability ML deployments.
Qualifications & Skills
  • Bachelor’s or Master’s in Computer Science, Engineering, or a related field.
  • 5+ years of experience in ML engineering, MLOps, or platform engineering roles.
  • 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.
  • Proficiency in Python (PyTorch, Transformers, LangChain) and Terraform, with scripting experience in Bash or PowerShell.
  • Experience with Docker and Kubernetes, especially within Azure (AKS).
  • Familiarity with CI/CD principles, model registry, and ML artifact management using Azure ML and Azure DevOps Pipelines.
  • Working knowledge of vector databases, caching strategies, and scalable inference architectures.
  • Systems thinker who can design, implement, and improve robust, automated ML systems.
  • Excellent communication and documentation skills.
  • Strong problem‑solving mindset with a focus on delivery, reliability, and business impact.
Preferred Qualifications
  • 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 (Azure Solutions Architect, Azure AI Engineer, Terraform Associate) is a plus.
Salary & Benefits

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.

EEO Statement

Johnson Controls International plc. is an equal employment opportunity and affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, protected veteran status, genetic information, sexual orientation, gender identity, status as a qualified individual with a disability, or any other characteristic protected by law. To view more information about your equal opportunity and non‑discrimination rights as a candidate, please visit EEO is the Law. If you are an individual with a disability and you require an accommodation during the application process, please visit here.

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