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Mlops Data Engineer Jobs in Minnesota (NOW HIRING)

Ryan Companies

Senior Data Engineer

Minneapolis, MN · Hybrid

$11K - $144K/yr

The Senior Data Engineer will play a foundational role in building and maintaining the data ... Familiarity with MLOps or experience supporting machine learning pipelines in production ...

Allianz

Data Engineer Principal_3003

Minneapolis, MN · On-site

Experience with GenAI or ML platform integration (MLOps, feature engineering pipelines ... Deep knowledge of enterprise data governance patterns: audit trails, reconciliation, data quality ...

QBP

Sr Data Engineer BI

Bloomington, MN · Hybrid

$120K - $130K/hr

The Senior Data Engineer is a hands-on technical leader responsible for designing, building, and ... Operationalize ML models and AI agents through MLOps practices - model versioning, monitoring ...

Quality Bicycle Products

Sr Data Engineer BI

Bloomington, MN · On-site

$110K - $150K/yr

The Senior Data Engineer is a hands-on technical leader responsible for designing, building, and ... Operationalize ML models and AI agents through MLOps practices - model versioning, monitoring ...

Boston Scientific

Senior Data Engineer

Arden Hills, MN · On-site

$111K - $151K/yr

Ensure engineering knowledge - requirements, design history files, test data, quality records and ... Familiarity with MLOps/LLMOps practices, including data versioning and pipeline monitoring.

Boston Scientific

Senior Data Engineer

Arden Hills, MN

$111K - $151K/yr

Ensure engineering knowledge - requirements, design history files, test data, quality records and ... Familiarity with MLOps/LLMOps practices, including data versioning and pipeline monitoring ...

Boston Scientific

Senior Data Engineer

Arden Hills, MN · On-site

$111K - $151K/yr

Ensure engineering knowledge -- requirements, design history files, test data, quality records and ... Familiarity with MLOps/LLMOps practices, including data versioning and pipeline monitoring.

Boston Scientific

Senior Data Engineer

Arden Hills, MN · On-site

$107K - $145K/yr

Ensure engineering knowledge - requirements, design history files, test data, quality records and ... Familiarity with MLOps/LLMOps practices, including data versioning and pipeline monitoring.

Centraprise

ML Engineer

Minneapolis, MN · On-site

Understanding of ML system design (data leakage, training-serving skew, drift). * CI/CD and DevOps practices applied to ML workloads (MLOps). * Experience with feature stores, model registries, and ...

Target

Sr Engineer - MLOps Platform

Minneapolis, MN · On-site

$98K - $176K/yr

As a Sr Engineer on the MLOps Platform team, you will help design, build, and evolve an ... You will partner with Data Scientists, ML Engineers, product managers, and platform teams to build ...

Deloitte

AI Engineer Consultant

Minneapolis, MN · Hybrid

... and HR data domains. * 2+ years of experience operationalizing LLMOps/MLOps capabilities ... We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ...

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All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Minnesota

Mlops Data Engineer information

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 Minnesota?

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

What job categories do people searching Mlops Data Engineer jobs in Minnesota look for?

The top searched job categories for Mlops Data Engineer jobs in Minnesota are:

What cities in Minnesota are hiring for Mlops Data Engineer jobs?

Cities in Minnesota with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

AI/ML Data Integration Architect / Data Engineer (AI/ML)

Saransh Inc

Minneapolis, MN • On-site

Contractor

Re-posted 13 days ago

Job description

Role: Data Integration Architect / Data Engineer (AI/ML)
Location: Minneapolis, MN (Hybrid)
Job Type: Contract
 
Required 10+ years of experience
 
Position Summary:
  • We are looking for a highly skilled AWS + Databricks professional with a strong background in Artificial Intelligence / Machine Learning (AI/ML) and cloud-based data solutions. 
  • The ideal candidate will serve as a Solution Architect, leading technical designs and implementations across data pipelines, ML workflows, and scalable analytics platforms.
 
Responsibilities: 
  • Design and implement end-to-end ML solutions using AWS and Databricks
  • Architect and optimize data lakes / lakehouses using Delta Lake, S3, Glue, and Spark
  • Manage feature engineering, model training, evaluation, and deployment workflows via MLflow or SageMaker
  • Lead the architecture of scalable AI/ML pipelines
  • Collaborate with Data Engineers, MLOps teams, and business stakeholders to translate ML use cases into production systems
  • Enforce best practices for model governance, data security, and CI/CD in ML environments