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Ops Engineer Jobs in Wisconsin (NOW HIRING)

Techvilla Solutions

ML Ops Engineer

West Allis, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Franklin, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Butler, WI · On-site

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 ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

Techvilla Solutions

ML Ops Engineer

Lannon, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Waukesha, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Wales, WI · On-site

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 ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

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 learning infrastructure and deployment pipelines. The ideal candidate will have strong experience ...

Techvilla Solutions

ML Ops Engineer

Hubertus, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

North Lake, WI · On-site

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 ...

Techvilla Solutions

ML Ops Engineer

Nashotah, WI · On-site

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 ...

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Showing results 21-40

All JobsOps Engineer JobsOps Engineer Jobs in Wisconsin

Ops Engineer information

See Wisconsin salary details

$37.3K

$88K

$137.8K

How much do ops engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for ops engineer in Wisconsin is $88,035.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,200.00 and $98,400.00 per year, depending on experience, location, and employer.

What is the difference between Ops Engineer vs DevOps Engineer?

AspectOps EngineerDevOps Engineer
CredentialsTypically requires a degree in computer science or related field, with certifications like AWS, Linux, or CiscoSimilar credentials, often with additional certifications in automation tools and cloud platforms
Work EnvironmentFocuses on maintaining and supporting existing infrastructure, often in data centers or cloud environmentsInvolves automation, CI/CD pipelines, and collaboration between development and operations teams
Industry UsageCommonly used in IT operations, cloud services, and infrastructure managementWidely used in software development, cloud deployment, and continuous integration practices

While both roles require technical expertise in infrastructure and cloud platforms, Ops Engineers primarily focus on maintaining and supporting systems, whereas DevOps Engineers emphasize automation, deployment, and collaboration between development and operations teams.

How much do operations engineers make in the US?

Operations engineers in the US typically earn a median annual salary of around $80,000 to $110,000, depending on experience, location, and industry. Salaries can vary based on skills such as automation, scripting, and familiarity with cloud platforms or monitoring tools.

Is operations a high paying job?

Operations engineering is generally considered a well-paying role, especially for those with technical skills, experience, and certifications. Salaries vary by industry, location, and level of responsibility but tend to be competitive within engineering and technical fields.

What does an Ops Engineer do?

An Ops Engineer is responsible for managing and maintaining an organization’s IT infrastructure, including servers, networks, and cloud services. They automate deployment processes, monitor system performance, troubleshoot issues, and ensure system reliability and security using tools like scripting languages and monitoring platforms.
Ops Engineer jobs near you

ML Ops Engineer

West Allis, WI • On-site

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

Full-time

Posted 19 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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