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Google Cloud Machine Learning Engineer Jobs in Michigan

FastTek

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Machine Learning Engineer #1054987 * Employees in this job function are responsible for designing ... Google Cloud Platform - Familiarity with advanced GCP services beyond core compute and storage ...

FastTek

Machine Learning Engineer

Dearborn, MI · On-site

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 ...

New

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 ...

New

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/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 ...

Bespoke Labs

Machine Learning Engineer

Lansing, MI · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Ann Arbor, MI · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Detroit, MI · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Flint, MI · On-site

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

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

As of Jul 14, 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 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 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 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 July 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $114,007 per year, or $54.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

FastTek

Dearborn, MI

$105K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 16 hours ago

Job description

Machine Learning Engineer #1054987
Job Description:
  • Employees in this job function are responsible for designing, building, deploying, and scaling complex self-running ML solutions — including Generative AI and Large Language Model (LLM) systems — in areas such as computer vision, perception, localization, natural language processing, and conversational AI.
  • They automate and optimize the end-to-end ML and Gen AI model lifecycle using expertise in experimental methodologies, statistics, prompt engineering, and coding for tool building and analysis.
  • Design and develop innovative ML models, Gen AI systems, and software algorithms — including LLM-based architectures (e.g., transformer models, RAG pipelines, fine-tuned foundation models) — to solve complex business problems in both structured and unstructured environments

Skills Required:
GCP, Big Data, Artificial Intelligence & Expert Systems, API
  • GCP - Experience deploying and managing services on Google Cloud Platform, including Compute Engine, Cloud Storage, IAM, and Cloud Functions. For example, designing and implementing a cloud-native application architecture using GKE (Google Kubernetes Engine) with Cloud SQL and Pub/Sub.
  • Big Data - Experience working with large-scale data processing frameworks such as Apache Spark, Dataflow, or BigQuery. For example, building ETL pipelines that process terabytes of daily event data and transform it for downstream analytics.
  • Data Warehousing - Experience designing and maintaining data warehouse solutions (e.g., BigQuery, Snowflake, Redshift). For example, modeling a star schema for a retail analytics platform that supports reporting on sales, inventory, and customer behavior.
  • Artificial Intelligence & Expert Systems - Experience developing or integrating AI/ML models and rule-based expert systems. For example, building a classification model using Vertex AI to predict customer churn, or implementing a rule engine that automates underwriting decisions.
  • API - Experience designing, building, and consuming RESTful or gRPC APIs. For example, developing a versioned REST API with OAuth 2.0 authentication that serves as the integration layer between a mobile application and backend microservices.

Skills Preferred:
Google Cloud Platform
  • Google Cloud Platform - Familiarity with advanced GCP services beyond core compute and storage, such as Vertex AI, Dataflow, Cloud Composer (Airflow), and BigQuery ML. For example, using Cloud Composer to orchestrate scheduled data pipelines that feed into a BigQuery data warehouse.

Experience Required:
  • Senior Engineer Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang.; guides.
  • 10+ years in IT
  • 8+ years in development

Experience Preferred:
  • Strong understanding of Generative AI principles and architectures, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.
  • Proven experience in building and deploying RAG systems, including the use of **Vector Databases**.
  • Proficiency in Python programming.
  • Solid experience with SQL for data manipulation and querying.
  • Hands-on experience with Google Cloud Platform (GCP) services relevant to AI/ML.
  • Basic understanding and practical experience with Machine Learning model fine-tuning.
  • Familiarity with data engineering concepts and practices.
  • Expertise in prompt engineering techniques for interacting with LLMs.
  • Experience with the OpenAI SDK.
  • Experience developing robust APIs, preferably with **FastAPI**.
  • Proficiency with **version control systems (e.g., Git)**.
  • Experience with **containerization technologies (e.g., Docker)**.

Education Required:
  • Bachelor's Degree

Education Preferred:
  • Certification Program

Additional Information:
  • Design, build, maintain, and optimize scalable ML and Gen AI pipelines, architecture, and infrastructure, including vector databases, embedding stores, and LLM serving layers
  • Use machine learning and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis, and deep learning methods, alongside prompt engineering, retrieval-augmented generation (RAG), and parameter-efficient fine-tuning (PEFT/LoRA) to develop and evaluate algorithms that improve product/system performance, quality, data management, and accuracy
  • Adapt machine learning and Gen AI capabilities to domains such as virtual reality, augmented reality, object detection, tracking, classification, terrain mapping, intelligent document processing, and AI-powered agent workflows
  • Train, fine-tune, and re-train ML models and LLMs as required, including supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning
  • Deploy ML models, LLMs, and AI agents into production; run simulations and evaluations (including LLM evals and red-teaming) for algorithm development and test various scenarios
  • Automate model deployment, training, re-training, and Gen AI pipeline orchestration, leveraging principles of agile methodology, CI/CD/CT, MLOps, and LLMOps — including guardrail integration, prompt versioning, and observability tooling
  • Enable model management for model versioning, traceability, and governance — including responsible AI practices, bias evaluation, hallucination mitigation, and content safety controls — to ensure modularity and consistency across environments for both ML and Gen AI systems

Additional Info:
At FastTek Global, Our Purpose is Our People and Our Planet. We come to work each day and are reminded we are helping people find their success stories. Also, Doing the right thing is our mantra. We act responsibly, give back to the communities we serve and have a little fun along the way.
We have been doing this with pride, dedication and plain, old-fashioned hard work for 24 years!
FastTek Global is financially strong, privately held company that is 100% consultant and client focused.
We've differentiated ourselves by being fast, flexible, creative and honest. Throw out everything you've heard, seen, or felt about every other IT Consulting company. We do unique things and we do them for Fortune 10, Fortune 500, and technology start-up companies.
Our benefits are second to none and thanks to our flexible benefit options you can choose the benefits you need or want, options include:
  • Medical and Dental (FastTek pays majority of the medical program)
  • Vision
  • Personal Time Off (PTO) Program
  • Long Term Disability (100% paid)
  • Life Insurance (100% paid)
  • 401(k) with immediate vesting and 3% (of salary) dollar-for-dollar match

Plus, we have a lucrative employee referral program and an employee recognition culture.
FastTek Global was named one of the Top Work Places in Michigan by the Detroit Free Press in 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, and 2023!
To view all of our open positions go to: https://www.fasttek.com/fastswitch/findwork
Follow us on Twitter: https://twitter.com/fasttekglobal
Follow us on Instagram: https://www.instagram.com/fasttekglobal
Find us on LinkedIn: https://www.linkedin.com/company/fasttek
You can become a fan of FastTek on Facebook: https://www.facebook.com/fasttekglobal/
AI & Hiring Disclosure
We use AI tools to support parts of our hiring process, such as reviewing applications and identifying potential matches. These tools are designed to promote efficiency, consistency, and fairness, and they are always used under human oversight.
All personal data collected is used solely for recruitment purposes, and you have the right to know, access, or request deletion of your data at any time, subject to legal limits.
If AI will be used in a video interview, you'll be informed in advance and asked for your consent, with the option to opt out.
Our tools are regularly reviewed to detect potential bias and to ensure compliance with all applicable laws and our commitment to inclusive hiring.
To learn more or exercise your rights, please contact us at info@fasttek.com.