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Google Cloud Machine Learning Engineer Jobs in Wisconsin

AI & Machine Learning Engineer

Green Bay, WI · On-site

$94K - $129K/yr

AI & Machine Learning Engineer Work model:On-Site Location:Green Bay, WI, USA Shift:First shift Job ... Familiarity with cloud platforms (e.g., Azure, AWS, Google Cloud) and big data technologies.

Senior MLOps Engineer (Remote)

Menomonee Falls, WI · On-site

$104K - $144K/yr

... 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 ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

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Google Cloud Machine Learning Engineer information

See Wisconsin salary details

$23

$63

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How much do google cloud machine learning engineer jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for google cloud machine learning engineer in Wisconsin is $63.47, according to ZipRecruiter salary data. Most workers in this role earn between $54.09 and $72.31 per hour, depending on experience, location, and employer.

What is a Google Cloud Machine Learning engineer?

Google Cloud Machine Learning Engineers are professionals who design, build, and deploy machine learning models using Google Cloud Platform (GCP) services and tools. They work with large datasets, develop scalable ML solutions, and collaborate with data scientists and software engineers. Their role often includes automating data pipelines, optimizing model performance, and ensuring the reliability and security of ML deployments on the cloud. These engineers have expertise in both machine learning algorithms and cloud infrastructure, making them key contributors to data-driven projects.

What are the key skills and qualifications needed to thrive as a Google Cloud Machine Learning engineer?

To thrive as a Google Cloud Machine Learning Engineer, you need strong programming skills in Python or Java, a deep understanding of machine learning algorithms, and a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, TensorFlow, and relevant certifications like the Professional Machine Learning Engineer certification is highly valuable. Excellent problem-solving abilities, collaboration, and clear communication make someone stand out in this position. These skills and qualities are critical for designing, deploying, and optimizing scalable ML solutions that meet business objectives in cloud environments.

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

AspectGoogle Cloud Machine Learning EngineerData Scientist
Required CredentialsGoogle Cloud certifications, programming skills, ML knowledgeStatistics, data analysis, programming, often with advanced degrees
Work EnvironmentCloud platforms, coding, deploying ML modelsData analysis, modeling, reporting, often in research or business settings
Employer & Industry UsageTech companies, cloud service providers, enterprises using Google CloudVarious industries including finance, healthcare, marketing, research

Google Cloud Machine Learning Engineers focus on developing and deploying ML models on Google Cloud, requiring cloud certifications and coding skills. Data Scientists analyze data, build models, and generate insights, often with advanced degrees. While both roles work with data and ML, the Engineer role emphasizes cloud deployment and infrastructure, whereas Data Scientists focus on data analysis and modeling.

What are some typical cross-functional collaborations for a Google Cloud Machine Learning engineer?

As a Google Cloud Machine Learning Engineer, you'll frequently work alongside data scientists, software engineers, and product managers to design, deploy, and maintain machine learning solutions at scale. Collaboration often involves translating business requirements into machine learning pipelines, integrating models into cloud-based applications, and ensuring that solutions are robust, secure, and scalable. Regular communication with DevOps and infrastructure teams is also common to optimize model deployment and monitor performance. This cross-disciplinary teamwork is crucial for delivering impactful, production-ready AI solutions.
What are the most commonly searched types of Google Cloud Machine Learning Engineer jobs in Wisconsin? The most popular types of Google Cloud Machine Learning Engineer jobs in Wisconsin are:
What are popular job titles related to Google Cloud Machine Learning Engineer jobs in Wisconsin? For Google Cloud Machine Learning Engineer jobs in Wisconsin, the most frequently searched job titles are:
What cities in Wisconsin are hiring for Google Cloud Machine Learning Engineer jobs? Cities in Wisconsin with the most Google Cloud Machine Learning Engineer job openings:

AI & Machine Learning Engineer

Schneider

Green Bay, WI • On-site

$94K - $129K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

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


Schneider National rating

7.7

Company rating: 7.7 out of 10

Based on 102 frontline employees who took The Breakroom Quiz

107th of 359 rated logistics


Job description

AI & Machine Learning Engineer
Work model:On-Site
Location:Green Bay, WI, USA
Shift:First shift
Job level:Individual Contributor
Schedule:Full time; Mon-Fri 1st Shift
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Job overview:

Schneider is seeking an AI & Machine Learning Engineer in Green Bay to design and develop applications which enable AI-driven solutions to solve business problems. The AI & Machine Learning Engineer will work closely with senior engineers and data scientists to develop and maintain software solutions for data science initiatives.

Responsibilities:

  • Deploy and monitor machine learning models and algorithms in production both on-premises and in cloud environments.
  • Develop and optimize data processing and feature engineering pipelines.
  • Build APIs and microservices that support machine learning models.
  • Implement model performance monitoring and drift detection.
  • Write high-quality, efficient and well-documented code.
  • Conduct code reviews and mentor junior engineers on best practices for software development.
  • Perform data analysis and generate insightful reports to support business decisions.

Skills and qualifications:

  • Bachelor's degree in computer science, software engineering, data science, engineering, information systems or a related field.
  • A minimum of 2 years of experience in software engineering, data science or a related field in IT.
  • Proficient in programming languages such as Python, Java or C++.
  • Knowledge of data science libraries and frameworks like Pandas, NumPy and Scikit-learn.
  • Understanding of machine learning concepts, algorithms, model evaluation metrics and feature engineering.
  • Experience with SQL, database management and application development in a Linux server environment
  • Proficiency with version control systems (e.g., Git).
  • Familiarity with cloud platforms (e.g., Azure, AWS, Google Cloud) and big data technologies.
  • Familiarity with container platforms (e.g., Docker, Kubernetes), streaming platforms (e.g., Apache Kafka), ML Ops tools (e.g., MLFlow,) and CI/CD concepts.

Pay and benefits:

  • Medical, dental and vision insurance.
  • Company paid life insurance.
  • 401(k) savings plan with company match.
  • Paid time off and paid holidays.
  • Results-based incentive pay program where you can earn above and beyond your base pay.
  • Tuition reimbursement.
  • See full list of information technology benefits.

Schneider's inclusive culture

Our history has taught us that treating everyone with dignity and respect is vital to our ongoing success. We embrace and seek out diversity that is inclusive of thought, race, ethnicity, national origin, sex, gender, gender expression, age, religion, sexual orientation, ability, medical condition, veteran or military status, experience and background. This diversity and openness ensures all associates have equal access to opportunities and resources to contribute fully to the organization's success, and it fuels innovation, improves strategic thinking and cultivates leadership. Any applicant may request a reasonable accommodation to complete a job application, pre-employment testing, or job interview or to otherwise participate in the hiring process consistent with the Americans with Disabilities Act (ADA) by contacting their Recruiter, Human Resources Business Partner, and/or Human Resources Leave Administration.

Job ID: 262212

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