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Machine Learning Engineer Opt Jobs in Wisconsin (NOW HIRING)

KOHLS

MLOps Engineer II (Remote)

Menomonee Falls, WI · On-site

$97K - $134K/yr

Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including ... developing reusable frameworks and standardized solutions to streamline model implementation

Autodesk

$118K - $153K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

Autodesk

$107K - $139K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

Varsity Tutors

Machine Learning Tutor

Milwaukee, WI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Madison, WI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deloitte

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$103K - $141K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Insperity

Artificial Intelligence Engineer III

Madison, WI · On-site

$58 - $77.75/hr

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

$58 - $77.75/hr

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 ...

Exactsciences

Lead AI Platform Engineer

Madison, WI · On-site

$151K - $256K/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 ...

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Machine Learning Engineer Opt information

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What are popular job titles related to Machine Learning Engineer Opt jobs in Wisconsin? For Machine Learning Engineer Opt jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Wisconsin look for? The top searched job categories for Machine Learning Engineer Opt jobs in Wisconsin are:
Machine Learning Engineer Opt jobs near you
MLOps Engineer II (Remote)

MLOps Engineer II (Remote)

KOHLS

Menomonee Falls, WI • On-site

$97K - $134K/yr

Other

Posted 9 days ago

Kohl's rating

5.7

Company rating: 5.7 out of 10

Based on 1,447 frontline employees who took The Breakroom Quiz

13th of 21 rated department stores

Job description

About the Role

As MLOps Engineer II, you will focus on supporting cross-functional teams in designing, deploying, and operating machine learning solutions while building scalable infrastructure, tools, and best practices across the Machine Learning Engineering (MLE) ecosystem.

What You’ll Do

  • Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient model development through cloud infrastructure and tooling

  • Design, build, and maintain scalable machine learning infrastructure, including model serving (real-time and batch), training environments, and orchestration systems, with a focus on performance, scalability, and cost efficiency

  • Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including developing reusable frameworks and standardized solutions to streamline model implementation

  • Partner with and support Data Scientists by enabling effective use of cloud-based tools and infrastructure, and providing technical expertise across the ML lifecycle

  • Collaborate with machine learning engineers to share knowledge, improve best practices, and foster a culture of continuous learning and development

  • Support development and maintain monitoring, alerting, and automated testing frameworks to ensure the reliability, performance, and integrity of data pipelines, models, and infrastructure

  • Develop, document, and communicate implementations and best practices across the data science lifecycle

  • Manage and communicate cloud infrastructure costs and budgets to project stakeholders

  • Stay current with GCP services and evolving best practices in Machine Learning Engineering and MLOps

  • Additional tasks may be assigned

What Skills You Have

Required

  • Experience in MLOps or DevOps practices, including building and operating production ML systems using Docker, Kubernetes, CI/CD pipelines, Git-based version control, API development, model serving (batch and real-time), and automated testing frameworks

  • Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field

  • Experience working with Data Scientists to deploy, scale, and operationalize machine learning models in production environments

  • 3+ years of experience as a Machine Learning Engineer with a proven track record of successful project delivery

  • In-depth knowledge of cloud platform, preferably Google Cloud Platform services, particularly Vertex AI, BigQuery and Dataproc.

  • Extensive expertise with CI/CD and 

  • IaC best practices

  • Extensive knowledge of distributed computing and big data technologies like Spark, Kubeflow, Airflow and SQL

  • Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn)

  • Experience working in Agile environments with an emphasis on iterative development and continuous delivery

Preferred

  • Master’s Degree 

  • Proficiency in Java or other languages

  • Retail experience

  • E-commerce experience

  • 5+ years of experience in Machine Learning

  • Experience with optimization techniques and tools (e.g., Gurobi, linear programming, mixed-integer programming)

  • Experience working with agent based or agentic AI systems, including orchestration of autonomous workflows or LLM-driven agents

What Kohl's employees say

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Hours and flexibility

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