Machine Learning Engineer Jobs in Minnesota
Machine Learning Engineer jobs in Minnesota are in strong and growing demand, concentrated in financial services, healthcare technology, retail analytics, and enterprise software, with openings at every level from junior ML engineer to principal and staff. Minneapolis and Saint Paul anchor the majority of hiring, with Rochester a secondary hub driven by healthcare AI, and employers like UnitedHealth Group, Target, and U.S. Bank maintaining consistent, large-scale ML teams in the state. The most in-demand specialties are natural language processing, recommendation systems, and MLOps infrastructure. Scan the live roles below and apply to whichever ones fit.
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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.
JOIN TARGET AS A LEAD AI ENGINEER - ADANCED AI
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:
Target’s Advanced AI team builds end-to-end AI/ML systems that create meaningful business value across the enterprise. These systems may be powered by LLMs, classical machine learning, or deep learning models, and are designed as scalable, reliable, production-grade applications, including agentic architectures where they add clear value.
As a Lead AI Engineer for Advanced AI, you will help design, build, deploy, and maintain AI/ML applications that support automation, insight, and action across core business workflows. You will work closely with Data Scientists, engineers, product partners, platform teams, security teams, and business stakeholders to turn ambiguous business problems into practical, scalable technical solutions.
In this role, you will provide hands-on technical leadership for AI engineering initiatives. You will contribute to architecture and design decisions, evaluate appropriate models, frameworks, and tools, write maintainable production-quality code, and help establish strong engineering practices across development, testing, deployment, observability, documentation, and ongoing support. You will help ensure AI applications are secure, reliable, maintainable, and aligned to Target’s enterprise standards for infrastructure, platform architecture, data handling, and operational readiness.
You will also partner with senior engineers and engineering leaders to shape technical approaches, identify implementation risks, resolve roadblocks, and support the evolution of reusable AI engineering patterns. This role requires curiosity and continuous learning, including staying current with developments in AI, machine learning, LLMs, agentic systems, and modern software engineering practices. A successful Lead AI Engineer will help deliver production-grade AI applications that create measurable business value while raising the technical quality and capability of the broader team.
Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.
About you:
- 4-year degree in Quantitative disciplines (Science, Tech, Engineering, Mathematics) or equivalent industry experience required; MS in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics or a related technical field preferred
- 5+ years of hands-on software engineering experience, including experience building and operating production systems
- Strong experience developing AI/ML applications, including LLM-powered applications, agentic systems, applied machine learning solutions, data-intensive applications, or intelligent automation capabilities
- Strong proficiency with Python and experience with modern AI/ML or deep learning frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, Semantic Kernel, or similar tools
- Experience working with model APIs, prompt orchestration, agent development patterns, retrieval-augmented generation, evaluation frameworks, observability tools, cloud ML platforms, containers, or orchestration technologies
- Strong understanding of system design, application architecture, model and framework tradeoffs, experimentation, evaluation strategy, performance optimization, and production deployment considerations for AI systems
- Experience building scalable, maintainable, and well-tested services, APIs, data pipelines, applications, or platforms
- Experience with version control, CI/CD, code review practices, documentation, operational monitoring, and production support
- Ability to translate ambiguous business problems into clear technical approaches and collaborate with cross-functional partners to deliver practical solutions
- Strong communication skills, with the ability to explain technical concepts clearly to engineers, Data Scientists, product partners, business stakeholders, and leaders
- Ability to mentor engineers, contribute to technical direction, and raise the quality of engineering practices within a team
- Self-driven and results-oriented, with strong ownership, sound judgment, and the ability to move quickly while maintaining high technical standards
- Collaborative team player with a commitment to continuous learning, knowledge sharing, and building reliable AI systems that create business value
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_EAmericans 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.
Application deadline is : 11/19/2026See All 6 Machine Learning Engineer Jobs in Minnesota
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Find JobsMachine Learning Engineer Jobs by City in Minnesota
Where Minnesota roles are concentrated, by current openings.
Machine Learning Engineer Job Market in Minnesota
A snapshot from current Minnesota openings, updated as new roles post.
Who's Hiring



Top Industries Hiring
- Consulting & Professional Services
What Minnesota Employers Look For
The qualifications that appear most often in machine learning engineer jobs across Minnesota.
- Bachelor's or master's degree in computer science, statistics, or a closely related field
- Proficiency in Python and core ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience designing, training, and deploying machine learning models in production environments
- Familiarity with cloud platforms including AWS, Azure, or Google Cloud for ML workloads
- Strong foundation in statistics, linear algebra, and applied mathematics for model development
- Experience with data pipelines, feature engineering, and tools like Spark or SQL at scale
Machine Learning Engineer Jobs in Minnesota: Frequently Asked Questions
How do you become a machine learning engineer in Minnesota?
Machine learning engineering has no state-issued license in Minnesota, so the path runs through education and demonstrated technical skill. Most Minnesota employers expect at least a bachelor's degree in computer science, mathematics, or a related field, with a master's preferred at larger organizations like UnitedHealth Group or Target. Building a portfolio of deployed projects, contributing to open-source work, and earning cloud certifications from AWS or Google strengthens a candidacy considerably in this market.
How much do machine learning engineers make in Minnesota?
Machine learning engineers in Minnesota earn a median of about $130,050 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $79,900 for the lowest 10% to over $169,810 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire machine learning engineers in Minnesota?
Minnesota machine learning engineer roles are posted by Target, Wipro, and Kitware and others right now, based on current listings on Migrate Mate as of November 2026. Minnesota's concentration of large financial, healthcare, and retail headquarters means steady, recurring ML hiring rather than the boom-and-bust cycles common in startup-heavy markets.
Which Minnesota cities have the most machine learning engineer jobs?
Minneapolis, Brooklyn Park, and Saint Paul have the most machine learning engineer openings in Minnesota. The Minneapolis-Saint Paul metro drives the bulk of demand through its dense cluster of Fortune 500 headquarters in finance, retail, and healthcare technology, while Rochester's openings are shaped largely by the medical AI and clinical data work centered on its major healthcare institutions.
Are there remote machine learning engineer jobs in Minnesota?
Yes, and more than most fields. About 100% of machine learning engineer openings tied to Minnesota are remote or hybrid as of November 2026, reflecting how naturally the role fits distributed work. The most remote-friendly parts of the role are model development, experimentation, and data pipeline work, while production deployment and cross-functional collaboration roles tend to prefer at least some on-site presence.
How can I get hired as a machine learning engineer in Minnesota with little or no experience?
The most realistic entry path is a data analyst or data engineer role at a Minnesota employer, then transitioning internally once you've built ML project experience. UnitedHealth Group, Target, and U.S. Bank all run associate and rotational analytics programs that place new graduates close to ML teams. A strong GitHub portfolio, a completed Kaggle competition, or a cloud ML certification from AWS or Google signals readiness and consistently opens doors at Minnesota employers hiring entry-level talent.
Where can I find and apply to machine learning engineer jobs in Minnesota?
You can find and apply to machine learning engineer jobs in Minnesota on Migrate Mate, which lists current Minnesota openings. Search the available roles, find the ones that match your background and preferences, and apply directly to whichever ones fit.
See All 6 Machine Learning Engineer Jobs in Minnesota
Find roles in Minnesota that match your experience and apply in just a few clicks.
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