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Mlops Jobs in Minnesota (NOW HIRING)

Target

Sr Engineer - MLOps Platform

Minneapolis, MN

$98K - $176K/yr

As a Sr Engineer on the MLOps Platform team, you will help design, build, and evolve an enterpriseMLOpsplatform that enables teams to develop, deploy, andoperatemachine learning and Generative AI ...

XFORIA Inc

Mlops Engineer - only W2

Minneapolis, MN · On-site

$119K - $143K/yr

We recommend focusing on candidates with strong hands-on experience in Google Vertex AI-based batch processing pipelines . The ideal candidate should demonstrate expertise in the following areas: End ...

CSAA

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

Onsights

Senior Machine Learning Engineer

Minneapolis, MN · On-site

$109K - $149K/yr

... MLOps, distributed training, and edge inference technologies to enhance reproducibility, extensibility, scalability, and deployment speed of ML systems Qualifications : Required : • Bachelor ...

C4 Technical Services

AI/ML Engineer

Minneapolis, MN · On-site

AI/ML Engineering & MLOps Experience developing, evaluating, deploying, and monitoring ML/LLM solutions, including LLM evaluation metrics, hallucination reduction, safety guardrails, CI/CD, cloud ...

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Mlops information

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$98.6K

$154.8K

$184.1K

How much do mlops jobs pay per year?

As of Aug 23, 2026, the average yearly pay for mlops in Minnesota is $154,765.00, according to ZipRecruiter salary data. Most workers in this role earn between $146,228.00 and $168,090.00 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 Minnesota?

The most popular types of Mlops jobs in Minnesota are:

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

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

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

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

What cities in Minnesota are hiring for Mlops jobs?

Cities in Minnesota with the most Mlops job openings:

Mlops jobs near you
Infographic showing various Mlops job openings in Minnesota 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 $154,765 per year, or $74.4 per hour.

Sr Engineer - MLOps Platform

Target Brands, Inc.

Brooklyn Park, MN • On-site

$98K - $176K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

Target rating

6.6

Company rating: 6.6 out of 10

Based on 7,001 frontline employees who took The Breakroom Quiz

14th of 39 rated national retailers

Job description

The pay range is $98,000.00 - $176,000.00
Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.
About us:
Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.
About the Role:
As a Senior Engineer, you serve as a specialist in the engineering team that supports the product. You help develop and gain insight in the application architecture. You can distill an abstract architecture into concrete design and influence the implementation. You show expertise in applying the appropriate software engineering patterns to build robust and scalable systems. You are an expert in programming and apply your skills in developing the product. You have the skills to design and implement the architecture on your own, but choose to influence your fellow engineers by proposing software designs, providing feedback on software designs and/or implementation. You show good problem solving skills and can help the team in triaging operational issues. You leverage your expertise in eliminating repeat occurrences.
As a Sr Engineer on the MLOps Platform team, you will help design, build, and evolve an enterprise MLOps platform that enables teams to develop, deploy, and operate machine learning and Generative AI solutions at scale.
You will combine strong software engineering and platform engineering fundamentals with an understanding of ML and AI workflows. You will partner with Data Scientists, ML Engineers, product managers, and platform teams to build secure, reliable, and easy-to-use capabilities across the AI/ML lifecycle.
This is a hands-on engineering role focused on building platforms, services, and developer experiences that enable AI/ML teams to move from experimentation to production.
What You Will Do:
  • Design, build, test, and operate scalable services and capabilities for an enterprise MLOps platform.
  • Build APIs, microservices, and event-driven systems that support ML and Generative AI workflows.
  • Develop platform capabilities for model development, deployment, serving, monitoring, and lifecycle management.
  • Enable Generative AI use cases including LLMs, RAG, embeddings, vector search, and agentic applications through reusable platform capabilities.
  • Integrate with cloud AI/ML services, data platforms, model providers, and enterprise systems.
  • Build automation and self-service experiences that improve developer and Data Scientist productivity.
  • Implement observability, evaluation, governance, security, and reliability capabilities across the ML lifecycle.
  • Optimize platform services for scalability, availability, performance, and cost.
  • Apply strong engineering practices including automated testing, CI/CD, infrastructure automation, and operational excellence.
  • Collaborate across engineering, Data Science, product, security, and infrastructure teams and mentor other engineers through design and code reviews.

Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.
About You:
  • 5+ years of professional software engineering experience building and operating production systems.
  • Strong proficiency in Java or a comparable object-oriented programming language; experience with Python is beneficial.
  • Experience with REST APIs, microservices, distributed systems, SQL/NoSQL databases, Docker, Kubernetes, Git, and CI/CD.
  • Experience building or supporting platforms, developer tooling, or infrastructure services.
  • Understanding of the machine learning lifecycle, including experimentation, training, deployment, serving, monitoring, and model management.
  • Familiarity with MLOps practices and technologies for production ML systems.
  • Experience with cloud platforms; GCP preferred
  • Familiarity with Generative AI technologies including LLMs, RAG, embeddings, vector databases, and AI agents.
  • Experience with monitoring, observability, security, and reliability of production systems.
  • Ability to independently design and deliver scalable platform capabilities.
  • Strong communication and collaboration skills across engineering, Data Science, product, and platform teams.

Desired Qualifications:
  • Experience building or operating an enterprise MLOps or AI platform.
  • Experience with cloud ML platforms such as Gemini Enterprise Agent Platform (Vertex AI) or equivalent technologies.
  • Experience with Kubernetes-based ML infrastructure and model serving.
  • Experience enabling Generative AI capabilities through shared platforms or services.
  • Experience designing self-service developer platforms, SDKs, APIs, or tooling.

This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target's needs. A Hybrid/Flex for Your Day work arrangement means the team member's core role will need to be performed both onsite at the Target HQ MN location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Click here if you are curious to learn more about Minnesota.
Benefits Eligibility
Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_D
Americans with Disabilities Act (ADA)
In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.

What Target employees say

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About Target

Sourced by ZipRecruiter

We're here to help all families discover the joy of everyday life. Target is a general merchandise retailer with stores in all 50 U.S. states and the District of Columbia. 75% of the U.S. population lives within 10 miles of a Target store. We employ 400,000+ Our tagline is "Expect More. Pay Less." We've been using it since 1994! The Target Corporation also owns Shipt and Roundel. More to love! Target is headquartered in Minneapolis, Minnesota, its hometown since the first Target store opened in 1962 under The Dayton Company.

Industry

Retail and scientific research and development services

Company size

10,000+ Employees

Headquarters location

Minneapolis, MN, US

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