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

Epic

Software Engineer

Janesville, WI · On-site

... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ... Engineering, Computer Engineering, or a related field • A history of academic excellence or ...

Exactsciences

AI Intern - Co-op Fall 2026

Madison, WI · On-site

$35K - $56K/yr

The AI Intern will collaborate with data scientists, engineers, and cross-functional teams to research, prototype, and implement AI solutions-including machine learning (ML), deep learning (DL), and ...

New

Maximus

AI/ML Software Developer

Madison, WI · Remote

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

Maximus

AI/ML Software Developer

Whitewater, WI · Remote

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

Paradigm

Senior Applied AI Engineer

Middleton, WI · On-site

$127K - $187K/yr

The Senior Applied AI Engineer will design, deploy, and optimize AI systems that power next ... In this role, you'll build the bridge between machine learning models and real-world applications ...

State of Wisconsin

Data Engineer

Madison, WI · On-site +1

$82.13K - $102.60K/yr

... machine learning. The incumbent will serve as a subject matter expert as it relates to the Circuit ... data engineering experience. 3) Excellent knowledge of data modeling and data warehousing. 4) ...

New

CFS

AI Engineer

Madison, WI · Remote

$200K/yr

AI Engineer | Permanent | No Sponsorship Available | Remote ABOUT OUR CLIENT * The company is ... machine learning fundamentals * Practical experience with deep learning frameworks, RAG ...

CFS

AI Engineer

Waunakee, WI · Remote

$200K/yr

AI Engineer | Permanent | No Sponsorship Available | Remote ABOUT OUR CLIENT * The company is ... machine learning fundamentals * Practical experience with deep learning frameworks, RAG ...

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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 May 29, 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 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 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.

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 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 jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.

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
Machine Learning Scientist - AI Trainer

Machine Learning Scientist - AI Trainer

DataAnnotation

Oregon, WI • On-site, Remote

$40/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr

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