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Mlops Data Engineer Jobs in Milwaukee, WI (NOW HIRING)

KOHLS

Senior MLOps Engineer (Remote)

Menomonee Falls, WI · On-site

$104K - $144K/yr

Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient ...

Manpower Group

Data Scientist

Milwaukee, WI · On-site

Experience collaborating with Data Engineering, IT, Architecture, DevOps/MLOps, Product, and ... business stakeholders within Agile or Product-Oriented Delivery (POD) environments Education:

Manpower

Data Scientist

Milwaukee, WI · On-site

Experience collaborating with Data Engineering, IT, Architecture, DevOps/MLOps, Product, and ... business stakeholders within Agile or Product-Oriented Delivery (POD) environments Education:

ManpowerGroup

Data Scientist

Milwaukee, WI

Experience collaborating with Data Engineering, IT, Architecture, DevOps/MLOps, Product, and ... business stakeholders within Agile or Product-Oriented Delivery (POD) environments Education:

Techvilla Solutions

ML Ops Engineer

Colgate, WI

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

Techvilla Solutions

ML Ops Engineer

West Allis, WI

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

Techvilla Solutions

ML Ops Engineer

Franklin, WI

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

Techvilla Solutions

ML Ops Engineer

Butler, WI

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

Techvilla Solutions

ML Ops Engineer

Elm Grove, WI

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

Techvilla Solutions

ML Ops Engineer

Big Bend, WI · On-site

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

Techvilla Solutions

ML Ops Engineer

River Hills, WI

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

Techvilla Solutions

ML Ops Engineer

Glendale, WI

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

Techvilla Solutions

ML Ops Engineer

Bayside, WI

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

Techvilla Solutions

ML Ops Engineer

Cudahy, WI

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

Techvilla Solutions

ML Ops Engineer

New Berlin, WI

Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...

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All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Milwaukee, WI

Mlops Data Engineer information

See Milwaukee, WI salary details

$43.8K

$127.8K

$174.9K

How much do mlops data engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for mlops data engineer in Milwaukee, WI is $127,802.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,800.00 and $135,500.00 per year, depending on experience, location, and employer.

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

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

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What is the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.

What are popular job titles related to Mlops Data Engineer jobs in Milwaukee, WI?

For Mlops Data Engineer jobs in Milwaukee, WI, the most frequently searched job titles are:

What job categories do people searching Mlops Data Engineer jobs in Milwaukee, WI look for?

The top searched job categories for Mlops Data Engineer jobs in Milwaukee, WI are:

What cities near Milwaukee, WI are hiring for Mlops Data Engineer jobs?

Cities near Milwaukee, WI with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in Milwaukee, WI as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $127,802 per year, or $61.4 per hour.

Senior MLOps Engineer (Remote)

KOHLS

Menomonee Falls, WI • On-site

$104K - $144K/yr

Other

Re-posted 8 days ago

Key responsibilities

  • Collaborate with Data Scientists and Engineers to build, deploy, and operate machine learning solutions and pipelines.

  • Design, build, and maintain scalable machine learning infrastructure, including model serving, training environments, and orchestration systems.

  • Support development and maintenance of monitoring, alerting, and automated testing frameworks to ensure system reliability and performance.

Kohl's rating

5.8

Company rating: 5.8 out of 10

Based on 1,480 frontline employees who took The Breakroom Quiz

12th of 21 rated department stores

Job description

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, tools, and best practices across the Machine Learning Engineering (MLE) ecosystem.

What You’ll Do

  • Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient model development through cloud infrastructure and tooling

  • Design, build, and maintain scalable machine learning infrastructure, including model serving (real-time and batch), training environments, and orchestration systems, with a focus on performance, scalability, and cost efficiency

  • Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including developing reusable frameworks and standardized solutions to streamline model implementation

  • Partner with and support Data Scientists by enabling effective use of cloud-based tools and infrastructure, and providing technical expertise across the ML lifecycle

  • Collaborate with machine learning engineers to share knowledge, improve best practices, and foster a culture of continuous learning and development

  • Support development and maintain monitoring, alerting, and automated testing frameworks to ensure the reliability, performance, and integrity of data pipelines, models, and infrastructure

  • Develop, document, and communicate implementations and best practices across the data science lifecycle

  • Manage and communicate cloud infrastructure costs and budgets to project stakeholders

  • Stay current with GCP services and evolving best practices in Machine Learning Engineering and MLOps

  • Additional tasks may be assigned

What Skills You Have

Required

  • Experience in MLOps or DevOps practices, including building and operating production ML systems using Docker, Kubernetes, CI/CD pipelines, Git-based version control, API development, model serving (batch and real-time), and automated testing frameworks

  • Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field

  • Experience working with Data Scientists to deploy, scale, and operationalize machine learning models in production environments

  • 3+ years of experience as a Machine Learning Engineer with a proven track record of successful project delivery

  • In-depth knowledge of cloud platform, preferably Google Cloud Platform services, particularly Vertex AI, BigQuery and Dataproc.

  • Extensive expertise with CI/CD and 

  • IaC best practices

  • Extensive knowledge of distributed computing and big data technologies like Spark, Kubeflow, Airflow and SQL

  • Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn)

  • Experience working in Agile environments with an emphasis on iterative development and continuous delivery

Preferred

  • Master’s Degree 

  • Proficiency in Java or other languages

  • Retail experience

  • E-commerce experience

  • 5+ years of experience in Machine Learning

  • Experience with optimization techniques and tools (e.g., Gurobi, linear programming, mixed-integer programming)

  • Experience working with agent based or agentic AI systems, including orchestration of autonomous workflows or LLM-driven agents

What Kohl's employees say

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Benefits

Hours and flexibility

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