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Mlops Jobs in Wisconsin (NOW HIRING)

Qualysoft

Fur ein Enterprise-KI-Projekt wird ein erfahrener MLOps Engineer gesucht. Ziel ist der Aufbau und Betrieb regelkonformer, skalierbarer End-to-End Machine-Learning-Workflows von der Entwicklung bis ...

KOHLS

Senior MLOps Engineer (Remote)

Menomonee Falls, WI · On-site

$104K - $144K/yr

About the Role As Senior MLOps Engineer, you will focus on supporting cross-functional teams in designing, deploying, and operating machine learning solutions while building scalable infrastructure ...

AgileEngine, LLC.

WI · On-site

$140 - $190/hr

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

New

Caterpillar Brazil

WI · On-site

The role requires deep expertise in AI/ML architectures, cloud platforms, MLOps practices and the ability to translate complex requirements into concrete designs for a global enterprise. #J-18808 ...

New

Qualysoft

Der Fokus liegt auf Big-Data-Engineering , ML/LLM-Workloads , MLOps-Automatisierung sowie der nahtlosen Integration in das Microsoft-Okosystem. 520 - 560 a day Rahmenbedingungen Start: Marz/April ...

Paradigm

WI · On-site

$120 - $180/hr

Design, build, and maintain scalable MLOps solutions that support the end-to-end machine learning lifecycle, including model training, deployment, monitoring, and retraining. * Develop and optimize ...

Myparadigm

WI · On-site

$140 - $190/hr

Design, build, and maintain scalable MLOps solutions that support the end-to-end machine learning lifecycle, including model training, deployment, monitoring, and retraining. * Develop and optimize ...

CSAA

MLOps, Automation & Observability * Design and implement automation, monitoring, observability, and operational tooling to improve platform reliability and efficiency. * Develop and maintain ...

New

CSAA

MLOps, Automation & Observability * Design and implement automation, monitoring, observability, and operational tooling to improve platform reliability and efficiency. * Develop and maintain ...

New

CSAA

MLOps, Automation & Observability * Design and implement automation, monitoring, observability, and operational tooling to improve platform reliability and efficiency. * Develop and maintain ...

New

CSAA

MLOps, Automation & Observability * Design and implement automation, monitoring, observability, and operational tooling to improve platform reliability and efficiency. * Develop and maintain ...

New

Paradigm

Senior ML Ops Engineer

Middleton, WI · On-site

$123K - $170K/yr

What You Will Do: · Design, build, and maintain scalable MLOps solutions that support the end-to-end machine learning lifecycle, including model training, deployment, monitoring, and retraining. · ...

AllSTEM Connections

Principal AI Engineer

Milwaukee, WI · On-site

$197K - $208K/yr

GenAI & MLOps Governance • GenAI Orchestration: Design production-scale GenAI applications utilizing agentic architectures, multi-agent orchestration, and complex tool-calling patterns. • MLOps ...

DataRobot, Inc.

WI · On-site

$165 - $225/hr

Advise on DataRobot platform use and modern AI/ML development, including MLOps, model governance, and scaling AI initiatives. * Deliver Value: Ensure solutions are robust, scalable, and aligned with ...

New

Capgemini

WI · On-site

$120 - $160/hr

Define and build ML platforms and workflows with Amazon SageMaker, covering training, tuning, deployment, and MLOps.* Translate business needs into well‐architected AWS AI solutions, aligned with ...

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All JobsMlops JobsMlops Jobs in Wisconsin

Mlops information

See Wisconsin salary details

$92.7K

$145.4K

$173K

How much do mlops jobs pay per year?

As of Aug 20, 2026, the average yearly pay for mlops in Wisconsin is $145,450.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,426.00 and $157,972.00 per year, depending on experience, location, and employer.

What is MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.

What are the key skills and qualifications needed to thrive as an MLOps engineer?

To thrive as an MLOps Engineer, you need a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

Is MLOps in demand?

MLOps is a rapidly growing field as organizations increasingly adopt machine learning models in production. Professionals with skills in cloud platforms, automation, and tools like Kubernetes and Docker are highly sought after, reflecting strong industry demand for MLOps expertise.

Is MLOps outdated?

MLOps is an evolving field focused on deploying and managing machine learning models efficiently. It remains highly relevant as organizations increasingly adopt AI solutions, with skills in automation, cloud platforms, and monitoring tools in demand. Staying current with new tools and best practices is essential for MLOps professionals.

What is the average salary in MLOps?

The average salary for MLOps engineers typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in cloud platforms, automation, and machine learning deployment tend to earn higher salaries.

What are the most commonly searched types of Mlops jobs in Wisconsin?

The most popular types of Mlops jobs in Wisconsin are:

What are popular job titles related to Mlops jobs in Wisconsin?

For Mlops jobs in Wisconsin, the most frequently searched job titles are:

What job categories do people searching Mlops jobs in Wisconsin look for?

The top searched job categories for Mlops jobs in Wisconsin are:

What cities in Wisconsin are hiring for Mlops jobs?

Cities in Wisconsin with the most Mlops job openings:

Mlops jobs near you
Infographic showing various Mlops job openings in Wisconsin as of August 2026, with employment types broken down into 100% Full Time. Highlights an 84% In-person, and 16% Remote job distribution, with an average salary of $145,450 per year, or $69.9 per hour.

MLOps Engineer

Qualysoft

Remote

Contractor

Re-posted 24 days ago

Job description

Fur ein Enterprise-KI-Projekt wird ein erfahrener MLOps Engineer gesucht. Ziel ist der Aufbau und Betrieb regelkonformer, skalierbarer End-to-End Machine-Learning-Workflows von der Entwicklung bis zum produktiven Einsatz.

Rahmenbedingungen
Start: ASAP
Laufzeit: Ende 2026, Verlangerung moglich
Auslastung: 100 %
Arbeitsmodell: Remote bevorzugt, gelegentliche Vor-Ort-Termine nach Absprache
400 - 450 a day
Aufgaben
Aufbau und Betrieb von End-to-End Data-Science- und ML-Workflows
Implementierung von ML-Orchestrierungslosungen (z. B. Kubeflow Pipelines)
Integration von ML-Tracking- und Experiment-Tools (MLflow, TensorBoard, o. A.)
Automatisierung von Training-, Deployment- und Monitoring-Prozessen
Entwicklung und Pflege von Python-basierten ML-Applikationen
Umsetzung von CI/CD- und GitOps-Prinzipien fur ML-Pipelines
Sicherstellung von Security & Schwachstellenmanagement fur Code, Container und Modelle
Betrieb und Weiterentwicklung produktiver KI-Anwendungen
Einbindung regulatorischer Rahmenbedingungen (z. B. AI Act, interne Policies, Kundenvorgaben)
Abstimmung mit Plattform-, Fach- und Projektteams inkl. Erwartungsmanagement

Anforderungen
Mehrjahrige Erfahrung als MLOps Engineer, ML Engineer oder Data Engineer
Sehr gute Kenntnisse in Kubernetes-/OpenShift-basierten Umgebungen
Erfahrung mit ML-Orchestrierung, ML-Tracking und Monitoring
Sehr gute Python-Kenntnisse
Sehr gute Deutsch und Englischkenntnisse
Interessiert?
Bitte senden Sie uns Ihren aktuellen Lebenslauf inklusive Ihrer Verfugbarkeit sowie Ihrer Stundensatzvorstellung. Wir freuen uns auf Ihre Ruckmeldung.
Sie konnen mich gerne uber Freelancermap per E-Mail unter elena.kahraman@qualysoft.com oder uber LinkedIn kontaktieren.
Vielen Dank fur Ihr Verstandnis! +43 699 14402417
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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