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Mlops Machine Learning Engineer Jobs in Mosinee, WI

Automation Engineer I

Schofield, WI · On-site

$77K - $95K/yr

As an Automation Engineer I for the Machine Development Center (MDC) with Greenheck Group, design ... Learning & Development * Rewards & Recognition * Wellbeing & Mental Health * Work-Life Balance

Automation Engineer I

Schofield, WI · On-site

$77K - $95K/yr

As an Automation Engineer I for the Machine Development Center (MDC) with Greenheck Group, design ... Learning & Development * Rewards & Recognition * Wellbeing & Mental Health * Work-Life Balance

Sr. Process Engineer

Rothschild, WI · On-site

$103K - $134K/yr

... learning and growth. The location in Rothschild, (Wisconsin, United States), is seeking talent to ... Key goals include: developing new strategic business that aligns with machine capabilities ...

Sr. Process Engineer

Rothschild, WI · On-site

$103K - $134K/yr

... learning and growth. The location in Rothschild, (Wisconsin, United States), is seeking talent to ... Key goals include: developing new strategic business that aligns with machine capabilities ...

Quality Intern

Mosinee, WI · On-site

$27/hr

... machine process line. Pay Rate * $27.00 per hour Requirements * Applicants must be currently ... Actively pursuing a Paper Science or Chemical Engineering degree program * Living in or willing to ...

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Mlops Machine Learning Engineer information

See Mosinee, WI salary details

$31.1K

$127.2K

$191.1K

How much do mlops machine learning engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for mlops machine learning engineer in Mosinee, WI is $127,199.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,300.00 and $153,100.00 per year, depending on experience, location, and employer.

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

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

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What cities near Mosinee, WI are hiring for Mlops Machine Learning Engineer jobs?

Cities near Mosinee, WI with the most Mlops Machine Learning Engineer job openings:

Infographic showing various Mlops Machine Learning Engineer job openings in Mosinee, WI as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $127,199 per year, or $61.2 per hour.

Lead AI Engineer -- Advanced AI (applied ML, LLMs, agentic AI, ML Ops)

Target

Stevens Point, WI • On-site

$132K - $286K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 26 days ago


Target rating

6.6

Company rating: 6.6 out of 10

Based on 7,050 frontline employees who took The Breakroom Quiz

14th of 39 rated national retailers


Job description

The pay range is $132,000.00 - $286,000.00

Pay is based on several factors which vary based on position.These include labor markets and in some instancesmay 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 - ADVANCED 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 end to end applied machine learning and of hands-on experience developing AI/ML applications
  • Experience building LLM-powered applications, agentic systems, applied machine learning solutions, data-intensive applications or intelligent automation capabilities
  • Demonstrated strong programming proficiency with Python and experience with modern AI/ML or deep learning frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, Semantic Kernel, etc.
  • 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, applied data scientists, Product partners, business stakeholder and leaders
  • Ability to mentor AI engineers, contribute to technical direction and raise the quality of engineering practices within the 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_E

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.

Application deadline is : 09/24/2026

What Target employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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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