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Ml Engineer Jobs in Wisconsin (NOW HIRING)

Paradigm

WI · On-site

$120 - $150/hr

We are looking for a Senior Applied ML Engineer to be part of revolutionizing these industries. We are looking for a Senior Applied ML Engineer to design, implement, and scale machine learning ...

New

NELNET BUSINESS SOLUTIONS

AI / ML Engineer

Madison, WI · Remote

Our AI / ML Engineer role sits at the center of that work: building, operating, and scaling the AI agents that automate processes, surface insights, and help our teams make better decisions faster.

New

Qualysoft

Der Fokus liegt auf Big-Data-Engineering , ML/LLM-Workloads , MLOps-Automatisierung sowie der nahtlosen Integration in das Microsoft-Okosystem. 520 - 560 a day Rahmenbedingungen Start: Marz/April ...

Qualysoft

Der Azure AI / ML Engineer unterstutzt Fachbereiche und IT-Teams bei der Umsetzung innovativer KI-Anwendungen und begleitet diese von der Anforderungsaufnahme bis zum produktiven Betrieb und ...

Qualysoft

Fur ein Enterprise-KI-Projekt wird ein erfahrener MLOps Engineer gesucht. Ziel ist der Aufbau und ... Kubeflow Pipelines) Integration von ML-Tracking- und Experiment-Tools (MLflow, TensorBoard, o. A ...

Johnson Controls

AI Engineer

Glendale, WI · On-site

This AI/ML Engineer role sits at the center of that transformation. You will do two things in roughly equal measure: build production AI/ML and GenAI capabilities directly into our smart building ...

Johnson Controls

AI Engineer

Glendale, WI · On-site +1

This AI/ML Engineer role sits at the center of that transformation. You will do two things in roughly equal measure: build production AI/ML and GenAI capabilities directly into our smart building ...

Accenture

Lead AI / ML Engineer

Milwaukee, WI · On-site

$101K - $133K/yr

As a Responsible AI Engineer, you'll be experienced in building state of the art models to solve difficult business challenges. But you'll also have at least a year's experience looking at ...

New

Myparadigm

WI · On-site

$140 - $190/hr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are building the future with modern software engineering, agent-assisted systems, and mobile-first ...

New

Paradigm

WI · On-site

$120 - $180/hr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are building the future with modern software engineering, agent-assisted systems, and mobile-first ...

New

Paradigm

Senior ML Ops Engineer

Middleton, WI · On-site

$123K - $170K/yr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are building the future with modern software engineering, agent-assisted systems, and mobile-first ...

KLA-Belgium

WI · On-site

$79.93 - $125.60/hr

## Software Engineer - AI/MLApplylocations: Leuven, Belgiumtime type: Full timeposted on: Posted ... AI/ML Solution Development:** Design, develop, and implement machine learning models and AI ...

New

Johnson Controls

Ai Engineer

Milwaukee, WI

Data, ML & Software Engineering * Build and maintain the data pipelines that feed AI systems-ingestion, transformation, and ETL across structured and unstructured sources (e.g., Snowflake, Azure)

Johnson Controls

Ai Engineer

Milwaukee, WI · On-site

Data, ML & Software Engineering * Build and maintain the data pipelines that feed AI systems-ingestion, transformation, and ETL across structured and unstructured sources (e.g., Snowflake, Azure)

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All JobsMl Engineer JobsMl Engineer Jobs in Wisconsin

Ml Engineer information

See Wisconsin salary details

$33.3K

$90K

$143.3K

How much do ml engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for ml engineer in Wisconsin is $90,017.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,100.00 and $110,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an ML engineer?

To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.

Are machine learning engineers still in demand?

Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often find opportunities in tech, finance, healthcare, and other sectors investing in AI solutions.

What is an ML engineer?

ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.

What is the difference between Ml Engineer vs Data Scientist?

AspectML EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDevelops, deploys, and maintains ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, startups, and enterprises deploying ML solutionsResearch institutions, tech firms, and industries relying on data analysis

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

What are some common challenges ML engineers face when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.
What are popular job titles related to Ml Engineer jobs in Wisconsin? For Ml Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Ml Engineer jobs in Wisconsin look for? The top searched job categories for Ml Engineer jobs in Wisconsin are:
Ml Engineer jobs near you
Infographic showing various Ml Engineer job openings in Wisconsin as of August 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $90,017 per year, or $43.3 per hour.

Senior Applied ML Engineer

Paradigm

WI • On-site

$120 - $150/hr

Other

Posted 3 days ago

New

Job description

Paradigm is a software company transforming the way that the residential, construction & building product industries operate across the globe. We are looking for a Senior Applied ML Engineer to be part of revolutionizing these industries.

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 techniques—ranging from computer vision to large language models—to automate critical workflows such as blueprint understanding, 3D model generation, and materials forecasting. This role blends research, engineering, and domain expertise to deliver practical, production-ready AI systems that transform how homes are designed, estimated, and built.

What You Will Do
  • Develop and optimize CNN and LLM-powered models for computer vision, document extraction, and automated construction workflows.
  • Prototype, fine-tune, and assess models for NLP tasks such as classification, entity recognition, and summarization of construction data.
  • Build scalable ML pipelines and backend services that integrate into production-grade agents and digital platforms.
  • Drive the end-to-end ML lifecycle: from experimentation and training, to deployment, monitoring, and continuous improvement.
  • Integrate retrieval, ML, and rules-based methods to deliver reliable, explainable, and supportable features.
  • Collaborate closely with product managers, software engineers, and construction domain experts to solve real-world challenges with measurable business impact.
What You Need to Succeed
  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field.
  • 5+ years of experience designing and deploying applied ML systems at scale.
  • Experience with computer vision (CNNs, object detection, segmentation) and natural language processing (LLMs, embeddings, transformers).
  • Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).
  • Experience with ML Ops platforms and deploying ML systems into production (MLflow, Kubeflow or equivalent).
  • Experience with APIs, CI/CD pipelines, cloud platforms (AWS/Azure/GCP).
  • Ability to clearly communicate technical concepts to both engineers and non-technical stakeholders.
  • Experience applying ML in construction, CAD/BIM, architecture, or digital twin platforms is preferred.
  • Familiarity with graph-based retrieval, RAG pipelines, or multimodal ML is preferred.
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