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Ml Engineer Jobs in Minnesota (NOW HIRING)

AI Engineer - AI/ML

Minnetonka, MN · Hybrid

$116K - $140K/yr

We are seeking a highly skilled and motivated AI/ML Engineer to lead innovations in claims adjudication through advanced Generative AI solutions. This role emphasizes Large Language Models (LLMs ...

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Ml Engineer information

See Minnesota salary details

$32.3K

$87.3K

$139.1K

How much do ml engineer jobs pay per year?

As of Sep 2, 2026, the average yearly pay for ml engineer in Minnesota is $87,347.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,100.00 and $106,800.00 per year, depending on experience, location, and employer.

What is an ML engineer?

ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.

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

To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.

What are some common challenges ML engineers face when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.

What is the difference between Ml Engineer vs Data Scientist?

AspectML EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDevelops, deploys, and maintains ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, startups, and enterprises deploying ML solutionsResearch institutions, tech firms, and industries relying on data analysis

While both roles involve working with data and machine learning, ML Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights to inform business decisions. The roles often overlap but differ in their core responsibilities and focus areas.

Are machine learning engineers still in demand?

Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often work in environments that emphasize continuous learning and adaptation. The demand is expected to remain strong as organizations increasingly rely on machine learning solutions for competitive advantage.

What does a machine learning engineer do?

A machine learning engineer designs, develops, and deploys machine learning models to solve specific problems using large datasets. They work with programming languages like Python or Java, utilize frameworks such as TensorFlow or PyTorch, and often collaborate with data scientists and software engineers to integrate models into applications.

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

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

What cities in Minnesota are hiring for Ml Engineer jobs?

Cities in Minnesota with the most Ml Engineer job openings:

Infographic showing various Ml Engineer job openings in Minnesota as of August 2026, with employment types broken down into 91% Full Time, 2% Part Time, and 7% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $87,347 per year, or $42 per hour.

Senior AI ML Engineer - Remote

UnitedHealth Group

Eden Prairie, MN • On-site, Remote

$124K - $164K/yr

Full-time

Retirement

Re-posted 15 days ago


UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

192nd of 898 rated healthcare providers


Job description

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.
Optum Health is a patient-centered care organization serving communities nationwide by enabling high-quality, fully accountable, value-based care as part of Optum's mission to help millions of people live healthier lives. The work you do with our team directly improves health outcomes by connecting people with the care, resources, and support they need to feel their best. Join us to start Caring. Connecting. Growing together.
Position Summary
As a Senior AI/ML Engineer within the Optum Health & Financial Tech AI team, you will design and build enterprise-scale generative AI applications and agentic workflows that solve complex health and financial technology challenges. You will collaborate with cross-functional partners to develop multi-step reasoning systems, implement advanced Retrieval-Augmented Generation (RAG) pipelines, and craft responsive, full-stack experiences using modern frameworks like React, Next.js, Python, and PostgreSQL. By deploying innovative AI technologies safely and responsibly, you will directly support our mission of delivering impactful, context-aware digital solutions that improve health outcomes and operational efficiency.
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.
Primary Responsibilities:
  • Design, develop, and deploy enterprise-scale AI-powered solutions and LLM-powered applications using modern GenAI frameworks and APIs with an emphasis on the responsible use of AI
  • Develop agentic AI workflows, multi-step reasoning systems (with tool usage and memory), and advanced Retrieval-Augmented Generation (RAG) pipelines
  • Design and develop responsive frontend applications using React and Nextjs, and build backend services, APIs, and microservices using Python and Nodejs
  • Build systems for document ingestion, chunking, embeddings, semantic search, and advanced retrieval strategies (hybrid search, GraphRAG, contextual enrichment)
  • Design and optimize relational data models using PostgreSQL and integrate vector databases with relational data sources for contextual responses
  • Define end-to-end architecture spanning frontend, backend, AI, and data layers, ensuring performance, scalability, and reliability
  • Lead technical decision-making, design reviews, and code reviews, while mentoring junior engineers in AI engineering and full-stack best practices
  • Use enterprise-approved AI tools to streamline developer workflows, automate tasks, and drive continuous improvement across the development lifecycle
  • Evaluate emerging AI trends, frameworks, tools, and technologies to inform solution design, strategic innovation, and technical direction
  • Collaborate with product, business, and engineering teams to translate complex business requirements into scalable technical designs, communicating complex AI concepts to non-technical stakeholders

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required Qualifications:
  • Bachelor's degree or equivalent experience (such as an additional 4+ years of software development experience in lieu of a degree)
  • 6+ years of professional experience in software engineering or AI/ML engineering
  • 4+ years of hands-on experience with frontend technologies (React, Nextjs) and backend development (Python or Nodejs, and REST APIs)
  • 3+ years of experience with relational database design and optimization using PostgreSQL
  • 2+ years of experience building and deploying end-to-end Generative AI and LLM-powered applications in production
  • 2+ years of experience designing and implementing RAG (Retrieval-Augmented Generation) pipelines, including semantic search, embeddings, and vector databases
  • 1+ years of experience with AI orchestration frameworks (such as LangChain, LangGraph, or CrewAI) or developing agentic, multi-agent AI workflows

Preferred Qualifications:
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field
  • Experience implementing hybrid search strategies, GraphRAG, and contextual enrichment patterns for document retrieval
  • Deep understanding of distributed systems, microservices architecture, and enterprise application scalability
  • Solid expertise in designing AI evaluation metrics and establishing safety guardrails for reliable model outputs
  • Proven ability to mentor engineering teams, lead technical design reviews, and establish best practices in full-stack and AI development
  • Proven excellent cross-functional communication skills, with the ability to translate complex technical AI concepts into clear business insights for stakeholders

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $120,100 - $214,500 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.
UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.
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