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Mlops Machine Learning Engineer Jobs in Mosinee, WI

4MINDS

Technical Recruiter

Wausau, WI · On-site +1

$110K - $125K/yr

Proven track record of building engineering teams from the ground up, hiring across different sales segments (product, engineering, machine learning, devOps). Ability to assess technical talent by ...

Acrisure

Senior AI Engineer

Stevens Point, WI

$101K - $139K/yr

... testing, MLOps, and observability You may be a great fit if you: Have 5-10+ years of hands-on ... Career growth and learning opportunities * ...and so much more! Please note: This list is not ...

Nelson Miller Group

Electrical Engineer

Wausau, WI · On-site

Our expertise spans Human-Machine Interface (HMI) solutions, value-added distribution, plastics ... Education/Learning Experience: Bachelor's degree in Electrical Engineering or related field, or an ...

Nelson Miller Group

Electrical Engineer

Wausau, WI · On-site

Our expertise spans Human-Machine Interface (HMI) solutions, value-added distribution, plastics ... Education/Learning Experience: Bachelor's degree in Electrical Engineering or related field, or an ...

Domtar

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 ...

Domtar

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 ...

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All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Mosinee, WI

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 Jul 26, 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.

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.

What are the key skills and qualifications needed to thrive as an MLOps Machine Learning Engineer, and why are they important?

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.
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:
Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops Machine Learning Engineer job openings in Mosinee, WI as of July 2026, with employment types broken down into 8% As Needed, 75% Full Time, and 17% Part Time. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $127,199 per year, or $61.2 per hour.
Principal Engineer - AI /ML Platform

Principal Engineer - AI /ML Platform

Target

Stevens Point, WI • On-site

$168K - $356K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 11 days ago

Target rating

6.6

Company rating: 6.6 out of 10

Based on 6,950 frontline employees who took The Breakroom Quiz

14th of 39 rated national retailers

Job description

The pay range is $168,000.00 - $356,000.00

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.

PRINCIPAL ENGINEER - AI PLATFORMS

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.

Target's AI Platform organization is building the next generation of enterprise AI capabilities that enable teams to develop, deploy, govern, and operate Machine Learning and Generative AI solutions at scale. Our platform powers AI innovation across the enterprise by providing secure, scalable, and reusable capabilities that accelerate development while maintaining enterprise standards for reliability, governance, and operational excellence.

As a Principal Engineer - ML Operations Platform, you will provide technical leadership in defining the architecture and evolution of our enterprise machine learning platform. You will work across engineering, data science, infrastructure, security, and product organizations to establish scalable patterns for developing, deploying, monitoring, and governing machine learning systems throughout their lifecycle.

This role is ideal for a technology leader who enjoys solving complex platform challenges, influencing engineering strategy, and building capabilities that enable hundreds of engineers and data scientists to deliver AI solutions efficiently and safely.

About the Role:

As a Principal Engineer, you will define the long-term architecture and technical direction for Target's ML Operations Platform. You will establish enterprise-wide standards for machine learning lifecycle management, deployment, governance, observability, and operational excellence while partnering with cross-functional engineering teams to modernize AI platform capabilities. You will influence architecture across multiple organizations, mentor senior engineers, evaluate emerging technologies, and guide strategic platform investments that improve developer productivity and accelerate AI adoption.

Key responsibilities include:

  • Define the long-term technical strategy and architecture for the enterprise ML Operations Platform.

  • Design scalable, secure, and resilient cloud-native platforms supporting machine learning workloads.

  • Establish best practices for model development, deployment, monitoring, and lifecycle management.

  • Lead architecture for enterprise machine learning infrastructure supporting batch, streaming, and real-time inference.

  • Drive adoption of cloud-native technologies, Kubernetes, and modern platform engineering practices.

  • Define standards for model governance, observability, reliability, explainability, and responsible AI.

  • Partner with infrastructure, security, and engineering teams to improve platform scalability, performance, and operational efficiency.

  • Evaluate emerging technologies and recommend architectural approaches that improve platform capabilities.

  • Mentor engineers and influence technical direction across multiple engineering organizations.

Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.

About You:

  • MS in Computer Science, Engineering, Mathematics, or related technical field with relevant software engineering experience

  • Extensive experience designing and delivering large-scale cloud-native platforms or distributed systems

  • Deep experience building and operating enterprise machine learning platforms and MLOps capabilities

  • Strong understanding of machine learning lifecycle management, deployment strategies, observability and production operations

  • Demonstrated experience with machine learning platforms and tooling such as Vertex AI, Kubeflow, MLflow, and/or equivalent technologies

  • Experience building developer platforms or internal platform products

  • Experience with distributed training, GPU infrastructure, and large-scale inference platforms

  • Experience with feature management, model governance, and responsible AI practices.

  • Familiarity with Generative AI platforms and infrastructure supporting foundation model workloads

  • Experience with Terraform, GitOps, service mesh technologies, and platform automation

  • Experience mentoring senior engineers and leading enterprise-scale modernization initiatives

  • Expertise designing Kubernetes-based platforms supporting AI and machine learning workloads

  • Strong understanding of software engineering best practices including CI/CD, infrastructure as code, observability, testing, and automation

  • Experience defining technical strategy, architectural standards and engineering best practices across multiple teams

  • Excellent communication and influencing skills with the ability to communicate complex technical concepts to engineering and business leaders

This position may be considered for a Remote or Hybrid (known internally at Target as "Flex for Your Day") work arrangement based on Target's needs. A Remote work arrangement means the team member worksfull-time from home oran alternatelocation that's not a Target location, does not have a desk at a Target location and may travel to HQ up to 4 times a year. A Hybrid/Flex for Your Day work arrangement means the team member's core role may be performed either remote or onsite at a Target location 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.

Benefits Eligibility

Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_F

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 : 08/20/2026

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

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