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Mlops Machine Learning Engineer Jobs in Madison, WI

Springs Window Fashions

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

Design, build, ship, and own enterprise AI and machine learning solutions in production. * Build ... Experience with MLOps, vector databases, orchestration frameworks, and AI observability platforms.

Springs Window Fashions

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

Design, build, ship, and own enterprise AI and machine learning solutions in production. * Build ... Experience with MLOps, vector databases, orchestration frameworks, and AI observability platforms.

Springs Window Fashions

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

Design, build, ship, and own enterprise AI and machine learning solutions in production. * Build ... Experience with MLOps, vector databases, orchestration frameworks, and AI observability platforms.

Abbott

Lead AI Platform Engineer

Madison, WI · On-site

$99K - $198K/yr

Position Overview The Lead Engineer, Artificial Intelligence is a pivotal position responsible for ... This role demands expertise in Machine Learning, Natural Language Processing, and emerging ...

Abbott

Lead AI Platform Engineer

Madison, WI · On-site

$99K - $198K/yr

Position Overview The Lead Engineer, Artificial Intelligence is a pivotal position responsible for ... This role demands expertise in Machine Learning, Natural Language Processing, and emerging ...

Abbott

Lead AI Platform Engineer

Madison, WI

$99K - $198K/yr

Position Overview The Lead Engineer, Artificial Intelligence is a pivotal position responsible for ... This role demands expertise in Machine Learning, Natural Language Processing, and emerging ...

Insperity

Artificial Intelligence Engineer III

Madison, WI · On-site

$58 - $77.75/hr

  • Medical

  • Dental

  • Vision

  • PTO

This role applies advanced software, data science, machine learning, and LLM engineering expertise to build AI powered applications, model driven solutions, and intelligently automated workflows. The ...

Insperity

Artificial Intelligence Engineer III

Madison, WI · On-site

$58 - $77.75/hr

  • Medical

  • Dental

  • Vision

  • PTO

This role applies advanced software, data science, machine learning, and LLM engineering expertise to build AI powered applications, model driven solutions, and intelligently automated workflows. The ...

Insperity

Artificial Intelligence Engineer III

Madison, WI · On-site

$58 - $77.75/hr

  • Medical

  • Dental

  • Vision

  • PTO

This role applies advanced software, data science, machine learning, and LLM engineering expertise to build AI powered applications, model driven solutions, and intelligently automated workflows. The ...

Insperity

Artificial Intelligence Engineer III

Madison, WI · On-site

$58 - $77.75/hr

  • Medical

  • Dental

  • Vision

  • PTO

This role applies advanced software, data science, machine learning, and LLM engineering expertise to build AI powered applications, model driven solutions, and intelligently automated workflows. The ...

Urus

AI Engineer

Watertown, WI · On-site

Model Fine-Tuning & MLOps * Integrate, deploy, fine tune and monitor models in production using ... Strong knowledge of Large Language Models, Generative AI, NLP, and Machine Learning concepts. (3+ ...

Urus Group LP

AI Engineer

Watertown, WI · On-site +1

Model Fine-Tuning & MLOps * Integrate, deploy, fine tune and monitor models in production using ... Strong knowledge of Large Language Models, Generative AI, NLP, and Machine Learning concepts. (3+ ...

Farm Systems

AI Engineer

Watertown, WI · On-site

Model Fine-Tuning & MLOps * Integrate, deploy, fine tune and monitor models in production using ... Strong knowledge of Large Language Models, Generative AI, NLP, and Machine Learning concepts. (3+ ...

AgSource

AI Engineer

Watertown, WI · On-site +1

Model Fine-Tuning & MLOps * Integrate, deploy, fine tune and monitor models in production using ... Strong knowledge of Large Language Models, Generative AI, NLP, and Machine Learning concepts. (3+ ...

AgSource

AI Engineer

Watertown, WI · On-site

Model Fine-Tuning & MLOps * Integrate, deploy, fine tune and monitor models in production using ... Strong knowledge of Large Language Models, Generative AI, NLP, and Machine Learning concepts. (3+ ...

Paradigm

Senior Applied ML Engineer

Middleton, WI · Remote

$125K - $183K/yr

We are looking for a Senior Applied ML Engineer to design, implement, and scale machine learning systems that power next-generation construction and digital twin solutions. You will apply advanced ML ...

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Showing results 21-40

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

Mlops Machine Learning Engineer information

See Madison, WI salary details

$31.7K

$129.8K

$195K

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

As of Aug 12, 2026, the average yearly pay for mlops machine learning engineer in Madison, WI is $129,751.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,300.00 and $156,200.00 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?

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 are popular job titles related to Mlops Machine Learning Engineer jobs in Madison, WI? For Mlops Machine Learning Engineer jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Mlops Machine Learning Engineer jobs in Madison, WI look for? The top searched job categories for Mlops Machine Learning Engineer jobs in Madison, WI are:
What cities near Madison, WI are hiring for Mlops Machine Learning Engineer jobs? Cities near Madison, 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 Madison, WI as of August 2026, with employment types broken down into 1% As Needed, 66% Full Time, 30% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $129,751 per year, or $62.4 per hour.

Senior AI Engineer

Springs Window Fashions

Middleton, WI • On-site

$107K - $147K/yr

Other

Re-posted 10 days ago

Springs Window Fashions rating

6.7

Company rating: 6.7 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

Job description

Description
The Best Experience Company
Our tagline is "The Best Experience Company." More than just a set of words, it represents the essence of who we are at Springs Window Fashions. As North America's premier window covering company, we're committed to creating the Best Experience for our associates, consumers and end users, business partners, and communities. We want you to join our team of passionate self-starters who believe the world is full of Best Experience opportunities. So, if you're excited about the thought of a Best Experience career with a team focused on creating Best Experiences for all, we want to hear from you!
Position Summary
This is an engineering role, not a research role. The Sr AI Engineer is a hands-on technical leader who ships enterprise-scale AI into production and owns the architecture, governance, and engineering practices that turn ambitious ideas into working systems. You will drive AI adoption across the organization, mentor other engineers by building alongside them, and partner directly with Information Technology, business stakeholders, operations, customer service, product development, and analytics teams to deliver AI capabilities that measurably improve efficiency, elevate customer experiences, and sharpen decision making.
The ideal candidate is a software engineer first who happens to be obsessed with AI, pairing strong engineering fundamentals with hands-on command of machine learning, generative AI, data engineering, automation, and cloud technologies. You move fast and iterate in the open, treating a rough prototype that works as more valuable than a polished plan that doesn't. You thrive in a fast-paced, transformation-oriented environment and consistently turn business problems into production-ready AI solutions rather than pilots that stall in a notebook.
Key Responsibilities
  • Design, build, ship, and own enterprise AI and machine learning solutions in production.
  • Build and operationalize generative AI applications using large language models (LLMs), retrieval-augmented generation (RAG), copilots, and intelligent automation that real people across the business actually use.
  • Partner with business leaders to find and prioritize the highest-value AI use cases, and have the judgment to say no to the ones that aren't.
  • Stand up scalable AI pipelines, APIs, and integrations with enterprise platforms and business applications quickly, then improve them in the open.
  • Collaborate with data engineering teams to ensure high-quality, governed, and accessible data for AI initiatives.
  • Develop AI-enabled analytics and predictive models supporting manufacturing, supply chain, customer service, sales, and operations.
  • Implement AI governance, model monitoring, security, and responsible AI practices.
  • Optimize model performance, scalability, reliability, and operational efficiency.
  • Evaluate emerging AI tools almost as fast as they ship, and give a clear, honest read on what is real and what is hype before recommending enterprise adoption.
  • Drive rapid experimentation and prototyping across the organization, failing fast, learning faster, and moving to the next iteration.
  • Create technical documentation, operational procedures, and knowledge transfer materials.
  • Mentor other engineers by building alongside them, not by lecturing, and continually raise the bar on AI engineering practices.

Requirements
Required
  • 8-10+ years overall technology experience
  • 5+ years specifically building-not just studying-AI/ML systems
  • Proven track record deploying AI at enterprise scale in production, not pilots that stalled in a notebook
  • Experience leading technical initiatives or teams that people want to follow, not just report to
  • Strong experience with AI architecture and distributed systems
  • Hands-on experience operationalizing generative AI at scale: LLMs, RAG, copilots, and automation
  • Able to explain what you built to an executive in two sentences and to an engineer in two hundred

Preferred
  • Experience with Microsoft Copilot, Azure OpenAI, or enterprise generative AI platforms.
  • Manufacturing, supply chain, consumer products, or retail industry experience.
  • Experience with MLOps, vector databases, orchestration frameworks, and AI observability platforms.
  • Familiarity with data visualization and analytics platforms such as Power BI or Tableau.
  • Experience leading enterprise AI transformation initiatives.
  • AI governance frameworks
  • FinOps for AI workloads
  • Multi-cloud AI strategy
  • Experience building internal AI platforms or copilots

How We Work to Deliver a Best Experience: Our Culture
  • Highly valued leadership skills include:
    • Empowerment: Encourages innovation and continuous learning. Enables cross-functional collaboration and technical experimentation.
    • Ownership: Owns solutions end to end: if it breaks, you fix it; if it works, you make it better. Delivers secure, scalable, business-aligned AI with real urgency and strong execution discipline.
    • Leadership: Influences technical direction and promotes enterprise AI adoption. Communicates effectively with both technical and non-technical stakeholders.
    • One Springs Team: Collaborates across departments to drive shared business outcomes. Builds strong relationships and trust across the enterprise.
    • Continuous Innovation: Stays ahead of emerging AI trends and tools, separating genuine advances from hype. Relentlessly improves AI capabilities, automation, and operational maturity.
    • Speed: Ships iterative value through rapid build-and-deploy cycles, often turning a new technique into a working prototype within days. Balances that speed with the operational stability and governance an enterprise requires.

What Springs Window Fashions employees say

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Hours and flexibility

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