ZipRecruiter

Log In

1

Google Cloud Machine Learning Engineer Jobs in Michigan

FastTek

Machine Learning Engineer

Dearborn, MI

Machine Learning Engineer #1058742 Position Description: We are seeking an experienced AI Engineer ... Experience working with cloud platforms (GCP and/or AWS) * Strong understanding of SDLC, version ...

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Corning

As a Machine Learning Engineer, you will work within a collaborative technical team to build, deploy, monitor, and maintain machine learning solutions that create measurable business value. You will ...

Corning

$95K - $130K/yr

As a Senior Machine Learning Engineer, you will design, deploy, maintain, and improve robust ... What would be a plus? - Experience with Databricks, MLflow, Kubeflow, Docker, Kubernetes, cloud or ...

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $180K/yr

As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning systems that control our mineral refining facilities. You'll start with well-scoped problems inside our ...

Saanvi Technologies

Machine Learning Engineer 3

Dearborn, MI · On-site

$105K - $126K/yr

Machine Learning Engineering Engineer 3 Dearborn, MI W2 Position Description: We are seeking an ... Experience building AI solutions on cloud platforms such as GCP and/or AWS. Strong understanding of ...

Stefanini

Machine Learning Engineer

Allen Park, MI · On-site

Stefanini is looking for a Machine Learning Engineer(Allen Park, MI) For quick apply, please reach out to Navneet Pathak at / We are looking for a candidate who is responsible for predicting and/ or ...

Domino's Pizza

Lead Machine Learning Engineer

Ann Arbor, MI · On-site

$100K - $132K/yr

Promote engineering best practices across software development, MLOps, and cloud-native platforms ... Develop and operationalize machine learning and Generative AI solutions that support business ...

next page

Showing results 1-20

All JobsGoogle Cloud Machine Learning Engineer JobsGoogle Cloud Machine Learning Engineer Jobs in Michigan

Google Cloud Machine Learning Engineer information

See Michigan salary details

$20

$54

$76

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

As of Aug 24, 2026, the average hourly pay for google cloud machine learning engineer in Michigan is $54.81, according to ZipRecruiter salary data. Most workers in this role earn between $46.73 and $62.45 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 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 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 the most commonly searched types of Google Cloud Machine Learning Engineer jobs in Michigan?

The most popular types of Google Cloud Machine Learning Engineer jobs in Michigan are:

What are popular job titles related to Google Cloud Machine Learning Engineer jobs in Michigan?

For Google Cloud Machine Learning Engineer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Google Cloud Machine Learning Engineer jobs in Michigan look for?

The top searched job categories for Google Cloud Machine Learning Engineer jobs in Michigan are:

What cities in Michigan are hiring for Google Cloud Machine Learning Engineer jobs?

Cities in Michigan with the most Google Cloud Machine Learning Engineer job openings:

Google Cloud Machine Learning Engineer jobs near you
Infographic showing various Google Cloud Machine Learning Engineer job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 22% Part Time, 2% Temporary, 2% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $114,007 per year, or $54.8 per hour.

Machine Learning Engineer (09235)

Talent Management Plus, Inc.

Detroit, MI • On-site

$110 - $170/hr

Other

Posted 12 days ago

Job description

Position: Machine Learning Engineer (09235)Location: Detroit, MIDuration: 6 months+Summary:

The Data Science and Analytics Center of Excellence (COE) is responsible for leading the creation and development of the overall strategy and direction of data science and advanced analytics – including ensuring continuity and seamless extension of existing programs, the development of a short- and long-term vision and roadmap, and defining and institutionalizing the role that data and analytics play throughout the organization as the fuel that drives and shapes client’s priorities and serves as an accelerant for client’s progress.

Description:

The ML Engineer is a key player in the Integrated Tech Programs & Strategies team. This role will be responsible for data engineering, data science Model deployment, testing and management for the end-to-end ML and data pipeline including data products. This role will leverage Client’s AI labs environment to enable the delivery in a common data lake and products.

Responsibilities:
  • Responsible for building and managing end-to-end data pipelines and operations from ingestion and integration through delivery for the data science prototypes and data products.
  • Adept at queries, report writing and presenting findings, analyze large complex datasets to extract insights and decide on the appropriate technique.
  • Understand and use data and ML fundamentals, including data structures, algorithms, computability and complexity and computer architecture.
  • Collaborate with data engineers to build data and model pipelines, manage the infrastructure and data pipelines needed to bring code to production.
  • Provide support to engineers and product managers in implementing machine learning in the product.
  • Drive the design, building and launching of new data models and ML/Data pipelines in production.
  • Identify, analyze, and interpret trends or patterns in complex data sets.
  • Consulting with managers, Product owners to determine and refine machine learning objectives.
  • Transforming data science prototypes and applying appropriate ML tools and technologies.
  • Contribute and support the development of the overall data science and machine learning strategy and roadmap.
Required Skills:
  • Bachelor’s degree in computer science, or equivalent IT knowledge/experience.
  • 2+ years of relevant work experience in Data Analysis, Data Engineer, Data Science & Data Integration.
  • Must have strong data infrastructure, data engineering and Machine Learning skills
  • Must have a proven track record of leading and scaling data pipelines, ML Model deployments in a cloud/on prem/big data environment
  • Strong knowledge of and experience with reporting packages (Business Objects etc.), databases (SQL etc.), programming (XML, JavaScript, or ETL frameworks).
  • Programming languages: SQL, Spark, Python, R, Jupyter Notebooks, Java, Scala, C++
  • Data Exploration and ETL: Alteryx, Talend, H2O, Informatica, Data Stage, Azure Data explorer, Azure Data Factory.
  • Data Warehouse Solutions: Redshift, Snowflake, Postgres, Data Lake.
  • Big Data technologies: Azure, AWS, Hadoop, Spark, Hive, Kafka, Flume, NoSQL stores (HBase, Cassandra, DynamoDB, MongoDB).
  • Cloud storage: S3, GCS, ADLS, Blob.
  • Machine Learning: Cloudera Data Science Workbench, Azure ML, Amazon ML, Google AutoML, Vertex AI.
  • Data Visualization Solutions: MS Power BI, Looker, Tableau, Azure Streaming Analytics, Data Lake Analytics, Azure Time Series Insights, Azure Synapse Analytics.
  • CI/CD and Code Management: Git, Maven, Docker, Jenkins, Azure Dev Ops.
  • Experience working with Data engineering, Data science, ETL teams and managing implementing projects that utilize big data, advanced analytics, and machine learning technologies.
  • Hands-on experience in building data and ML pipelines from variety of sources such as data warehouses and in-memory OLAP models, as well as experience in NoSQL/cloud.
  • Strong understanding of data, ML Models, Big Data, Relational databases, streaming and batch data processing.
  • Knowledge of machine learning evaluation metrics and best practice.
  • Strong experience building end-to-end data view with focus on integration.
Preferred Skills:
  • Experience working with on-prem and cloud-based data warehouses
  • Experience with cloud-based personalization and machine-learning applications.
  • Experience working for consumer or business-facing digital brands.
#J-18808-Ljbffr

Apply