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Google Cloud Machine Learning Engineer Jobs in Detroit, MI

EPSoft Technologies

AI engineer

Dearborn, MI · On-site

$89K - $122K/yr

AI engineer Location: Dearborn, MI,48120- 2 days onsite in a week Employment Type: Full-time ... working with Google Cloud platform. * Experience with Python and have used Machine Learning ...

Stefanini

Cloud Engineer

Dearborn, MI · On-site

$51.25 - $68.50/hr

The ideal candidate is a hands-on cloud engineer with strong Google Cloud Platform infrastructure experience, Infrastructure-as-Code expertise, and a solid understanding of DevOps, SRE, security ...

Apex Systems

AI Engineer

Dearborn, MI · On-site

Google Cloud Platform (Google Cloud Platform) * Cloud-native application architecture * Platform engineering and AI infrastructure Machine Learning & AI * Applied machine learning experience ...

Stefanini

Cloud Engineer

Dearborn, MI · On-site

$51.25 - $68.50/hr

The ideal candidate will have strong expertise in Kubernetes, multi-cloud environments (AWS/Google Cloud Platform), Infrastructure as Code, automation, and platform engineering, with a focus on ...

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All JobsGoogle Cloud Machine Learning Engineer JobsGoogle Cloud Machine Learning Engineer Jobs in Detroit, MI

Google Cloud Machine Learning Engineer information

See Detroit, MI salary details

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

As of Aug 21, 2026, the average hourly pay for google cloud machine learning engineer in Detroit, MI is $57.54, according to ZipRecruiter salary data. Most workers in this role earn between $49.04 and $65.53 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 Detroit, MI?

The most popular types of Google Cloud Machine Learning Engineer jobs in Detroit, MI are:

What are popular job titles related to Google Cloud Machine Learning Engineer jobs in Detroit, MI?

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

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

The top searched job categories for Google Cloud Machine Learning Engineer jobs in Detroit, MI are:

Google Cloud Machine Learning Engineer jobs near you

AI engineer

EPSoft Technologies

Dearborn, MI • On-site

$89K - $122K/yr

Full-time

Re-posted 13 hours ago

Job description

Job Title: AI engineer

Location: Dearborn, MI,48120- 2 days onsite in a week

Employment Type: Full-time

Position Description:

GDI&A is looking for a Software Engineer focused on building and driving the strategy forward for our internal AI/ML platform. This role will work in a small, cross-functional teams. The position will collaborate directly and continuously with business partners, product managers and designers, and will release early and often. The team you will be working on supports ML Practitioners and Data Scientists in their Mach1ML (Ford’s AI/ML platform similar to Uber’s Michelangelo, Facebook’s FBLearner, etc) on GCP journey or other ML Engineering / MLOps / Generative AI - LLM tasks, focusing on Mach1ML adoption and AI/ML democratization.

Skills Required:

• Work closely with Tech Anchor, Product Manager and Product Owner to deliver machine learning use cases using Agile Methodology.

• Work with other Software and ML Engineers to tackle challenging AI problems.

• Participate in Pair Programming for cross training/upskilling, problem solving, and speed to delivery.

• Leverage latest ML and GCP technologies.

• Work with Architects to make technical decision on tools, integration, and other issues.

• Drive PoCs/Discoveries of new tools and technologies to support robust ML Platform

• Collaborate with other software engineers to understand platform vision, break out tasks and help them solve complex issues.

• Grow technical capabilities / expertise and provide guidance to other software engineers on the team.

Skills Preferred:

• Experience working with Google Cloud platform.

• Experience with Python and have used Machine Learning algorithms (pytorch, NLP etc) .

• Experience using orchestration tools like Airflow and have knowledge of Infrastructure as code (Terraform).

• Experience working with container technology, docker files, docker images, GitHub, CI/CD concepts, Kubernetes (k8).

• Experience with Generative AI – LLM and building frontend with React / Chainlit / Streamlit.

• Experience in supporting continuous improvement by investigating development alternatives.

• Experience in Software Craftsmanship such as Paired Programming, Test Driven Development, DevOps etc.

• Experience in creating an API service with Fast API / Flask.

• Experience applying Agile practices to solution delivery.

• Must be a self-starter to understand existing bottlenecks and come up with innovative solutions.

• Open to learning new technology.

• Strong communication and presentation skills, ability to share/teach others, work collaboratively with others.

• Good understanding of cloud design considerations and limitations and impact of pricing.

Experience Required:

• 4+ years of experience in Python and Machine Learning Technologies.

• 2+ years of experience in Generative AI - LLM.

• 3+ years of work experience as a software engineer with exceptional software engineering knowledge.

• Experience working with Google Cloud Platform or other cloud experience. CICD tools (Tekton / Cloud Build / Airflow etc.) experience.