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Google Cloud Machine Learning Engineer Jobs in Wisconsin

TTEC

German-speaking Digital Cloud Engineer

Krakow, WI

$54.50 - $72.75/hr

Interesse an oder Grundkenntnisse in den Bereichen Google Cloud Professional Data Engineer oder Google Cloud Professional Machine Learning Engineer werden sehr geschtzt. * Tiefgehende Kenntnisse in ...

Autodesk

$107K - $139K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... Experience with cloud providers (e.g., AWS, Azure, Google Cloud Platform) * Experience testing ML ...

Autodesk

$118K - $153K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... Experience with cloud providers (e.g., AWS, Azure, Google Cloud Platform) * Experience testing ML ...

Serve Robotics

$225K - $260K/yr

... and point cloud data). This includes ensuring data is efficiently loaded, distributed, and ... Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a ...

Indeed

Senior Machine Learning Engineer

Milwaukee, WI

$103K - $141K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

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Google Cloud Machine Learning Engineer information

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$23

$63

$88

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

As of Jun 15, 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 are Google Cloud Machine Learning Engineers?

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, and why are they important?

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 salary of an aiml engineer in Google?

A Google Cloud Machine Learning Engineer typically earns a salary ranging from $120,000 to $180,000 annually, depending on experience, location, and level within the company. Compensation may also include bonuses, stock options, and benefits, with higher salaries often associated with advanced skills in cloud platforms and machine learning frameworks.

How much do machine learning engineers make at GCP?

Machine learning engineers at Google Cloud Platform (GCP) typically earn between $120,000 and $180,000 annually, depending on experience, location, and level. Salaries can increase with specialized skills in cloud services, data modeling, and certifications like Google Cloud Professional Machine Learning Engineer.

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 engineers make $500,000?

Senior engineers in high-demand fields such as software development, data science, and machine learning can earn $500,000 or more annually, especially with extensive experience, specialized skills, and leadership roles. Roles like senior software engineers, machine learning engineers, and technical architects often reach this compensation level in large tech companies or through equity and bonuses.

Does Google hire machine learning engineers?

Yes, Google hires machine learning engineers to develop and implement AI and machine learning solutions across various products and services. These roles typically require expertise in programming, data analysis, and familiarity with tools like TensorFlow and Google Cloud Platform.

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 job categories do people searching Google Cloud Machine Learning Engineer jobs in Wisconsin look for? The top searched job categories for Google Cloud Machine Learning Engineer jobs in Wisconsin 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:
Google Cloud Machine Learning Engineer jobs near you
Big Data Engineer || Remote

Big Data Engineer || Remote

Cerebra Consulting Inc

Milwaukee, WI • Remote

$55 - $72.75/hr

Other

Posted 5 days ago

Job description

Cerebra Consulting Inc is a System Integrator and IT Services Solution provider with a focus on Big Data, Business Analytics, Cloud Solutions, Amazon Web Services, Salesforce, Oracle EBS, Peoplesoft, Hyperion, Oracle Configurator, Oracle CPQ, Oracle PLM and Custom Application Development. Utilizing solid business experience, industry-specific expertise, and proven methodologies, we consistently deliver measurable results for our customers. Cerebra has partnered with leading enterprise software companies and cloud providers such as Oracle, Salesforce, Amazon and able to leverage these partner relationships to deliver high-quality, end-to-end customer solutions that are targeted to the needs of each customer.

Role : Big Data Engineer

100% Remote

Contract to hire

W2 Only

First Round Interview 60 minutes TEAMS coding exercise

Second Round Interview 90 minute interview, they will actually have you do a paired programming session to see how you interact and what your thought process is when going through the code

Must Have:

  • Python, SQL, Google Cloud Platform(BQ), Spark, Airflow
  • Google Cloud Platform Shop - using Big Query
  • Does NOT want a machine learning engineer, wants a big data engineer

Required Skills:

5-10 years of experience

Python, Airflow, PySpark, Spark SQL, Spark Streaming, Scala, Relational/No SQL databases, Apache Kafka, writing complex sql queries, Google Cloud Platform (Bigquery, Dataproc), working with RESTful APIs in data pipelines, CI/CD (gitlab CI)

Bonus Skills:

Experience with backend stack (Java, Springboot)

Thanks & Regards,

Himanshu Mishra | US IT Recruiter? | Cerebra Consulting Inc,

270 Lancaster Ave, Suite-D2, Malvern, PA 19355

Contact : EXT : 122

Email :

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