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Azure Ml Engineer Jobs (NOW HIRING)

Techvilla Solutions

ML Ops Engineer

Vernon, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Richfield, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Saint Francis, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Delafield, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Genesee Depot, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Mequon, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Brookfield, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Milwaukee, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Germantown, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Thiensville, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Pewaukee, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Merton, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Hales Corners, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Glendale, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

River Hills, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Cudahy, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Whitefish Bay, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

West Milwaukee, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Bayside, WI

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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All JobsTechnology JobsData JobsData Scientist JobsAzure Ml Engineer Jobs

Azure Ml Engineer information

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$39K

$101.8K

$137.5K

How much do azure ml engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for azure ml engineer in the United States is $101,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $116,500.00 per year, depending on experience, location, and employer.

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 are hiring for Azure Ml Engineer jobs?

Cities with the most Azure Ml Engineer job openings:

What states have the most Azure Ml Engineer jobs?

States with the most job openings for Azure Ml Engineer jobs include:

What are popular job titles related to Azure Ml Engineer jobs?

For Azure Ml Engineer jobs, the most frequently searched job titles are:

Azure Ml Engineer jobs near you

ML Ops Engineer

Vernon, WI • On-site

Techvilla Solutions
IT Services • 51 - 200 employees
Learn more about Techvilla Solutionsexternal

Full-time

Posted 20 days ago

Job description

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine learning infrastructure and deployment pipelines. The ideal candidate will have strong experience with cloud platforms, CI/CD, containerization, model deployment, monitoring, and ML lifecycle management.

Roles and Responsibilities
  • Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining.
  • Automate ML workflows using CI/CD, infrastructure as code, and workflow orchestration.
  • Deploy and manage machine learning models across cloud and on-premise environments.
  • Implement model versioning, experiment tracking, feature management, and model governance.
  • Build scalable infrastructure using Docker, Kubernetes, and cloud services.
  • Monitor model performance, data quality, system health, and production workloads.
  • Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams.
  • Troubleshoot production ML systems and optimize reliability, scalability, and performance.
  • Implement security, access controls, logging, and compliance best practices.
Required Skills
  • 5+ years of experience in DevOps, ML Engineering, MLOps, or a related field.
  • Strong experience with MLOps concepts and ML lifecycle management.
  • Hands-on experience with Python and scripting.
  • Experience with AWS, Azure, or GCP.
  • Strong knowledge of Docker and Kubernetes.
  • Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
  • Experience with MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, or similar ML platforms.
  • Experience with Git, Terraform, and infrastructure automation.
  • Knowledge of model monitoring, observability, data validation, and model performance tracking.
  • Strong understanding of REST APIs, microservices, Linux, and cloud-native architectures.
Preferred Skills
  • Experience with Apache Airflow, Databricks, Spark, or Kafka.
  • Knowledge of LLMOps/GenAI deployment and monitoring.
  • Experience with model serving frameworks such as KServe, Seldon, or NVIDIA Triton.
  • Familiarity with Prometheus, Grafana, ELK, or similar observability tools.
  • Understanding of ML security, governance, and responsible AI practices.
Education

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.

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