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Machine Learning Engineer Jobs in Madison, WI (NOW HIRING)

Springs Window Fashions

Senior AI Engineer

Middleton, WI

$107K - $147K/yr

The ideal candidate combines strong software engineering fundamentals with practical expertise in machine learning, generative AI, data engineering, automation, and cloud technologies. This ...

Springs Window Fashions

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

The ideal candidate combines strong software engineering fundamentals with practical expertise in machine learning, generative AI, data engineering, automation, and cloud technologies. This ...

Cliftonlarsonallen

Senior AI Engineer

Madison, WI · On-site

$105K - $144K/yr

This position blends applied machine learning, software engineering, cloud architecture, and end-to-end solution delivery. Success in this role requires a strong understanding that production AI ...

Wisconsin

Cloud Infrastructure Architect

Madison, WI · Remote

... AI, machine learning, and large-scale data analysis. Deployment Pipelines and Continuous Integration (CI/CD) Build and manage secure, automated CI/CD pipelines for data engineering workflows ...

DataAnnotation

SDLC Engineer - AI Trainer

Madison, WI · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

The Weather Channel

Senior Data Scientist

Madison, WI · On-site

Are you interested in applying machine learning or data mining on problems that truly improve ... Programming capabilities including C++, Java, Python is a plus but not necessary. Additional ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Madison, WI

Machine Learning Engineer information

See Madison, WI salary details

$31.7K

$129.8K

$195K

How much do machine learning engineer jobs pay per year?

As of Jul 10, 2026, the average yearly pay for 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 engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

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

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Madison, WI? The most popular types of Machine Learning Engineer jobs in Madison, WI are:
What are popular job titles related to Machine Learning Engineer jobs in Madison, WI? For Machine Learning Engineer jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Madison, WI look for? The top searched job categories for Machine Learning Engineer jobs in Madison, WI are:
What cities near Madison, WI are hiring for Machine Learning Engineer jobs? Cities near Madison, WI with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Madison, WI as of July 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $129,751 per year, or $62.4 per hour.
Senior AI Engineer

Senior AI Engineer

Springs Window Fashions

Middleton, WI

$107K - $147K/yr

Full-time

Re-posted 6 days ago

Springs Window Fashions rating

4.8

Company rating: 4.8 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

Job 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

The Sr AI Engineer serves as a technical leader responsible for enterprise-scale AI architecture, solution governance, and advanced AI engineering practices. This role drives strategic AI adoption and mentors engineering teams across the organization. This role will partner closely with Information Technology, business stakeholders, operations, customer service, product development, and analytics teams to deliver scalable AI capabilities that improve efficiency, enhance customer experiences, and enable data-driven decision making.

The ideal candidate combines strong software engineering fundamentals with practical expertise in machine learning, generative AI, data engineering, automation, and cloud technologies. This individual must be comfortable operating in a fast-paced, transformation-oriented environment and capable of translating business problems into production-ready AI solutions.

Key Responsibilities

  • Design, build, deploy, and maintain enterprise AI and machine learning solutions.
  • Develop and operationalize generative AI applications leveraging large language models (LLMs), retrieval-augmented generation (RAG), copilots, and intelligent automation.
  • Partner with business leaders to identify high-value AI use cases aligned to strategic priorities.
  • Build scalable AI pipelines, APIs, and integrations with enterprise platforms and business applications.
  • 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 technologies and recommend enterprise adoption strategies.
  • Support AI experimentation, rapid prototyping, and innovation initiatives across the organization.
  • Create technical documentation, operational procedures, and knowledge transfer materials.
  • Mentor technical teams and promote AI engineering best practices.

Required

  • Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
  • Advanced degree in Artificial Intelligence, Machine Learning, or Data Science preferred.
  • 8–10+ years overall technology experience
  • 5+ years focused in AI/ML engineering
  • Proven experience deploying enterprise-scale AI systems
  • Experience leading technical teams or major initiatives
  • Strong experience with AI architecture and distributed systems
  • Experience operationalizing generative AI at scale
  • Executive communication capability

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

  • Our Core Value: We do the right thing, always
  • Our Seven Cultural Behaviors
    • Empowerment - We trust our people.
    • Ownership - We take 100% responsibility for our roles actions, and results.
    • Leadership - We all lead by example and talk direct with respect (DWR).
    • One Team - We are One Springs Team.
    • Customer First - We consider our customers' needs before every decision.
    • Continuous Innovation - We are constantly learning, innovating, and improving.
    • Speed - We define priorities and operate with a sense of urgency and agility.

What Springs Window Fashions employees say

Pay

Hours and flexibility

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