ZipRecruiter

Log In

1

Google Machine Learning Engineer Jobs in Michigan

Wayve

Machine Learning Engineer, App SW

Detroit, MI · Hybrid

$283K - $381K/yr

In order to set you up for success as a Machine Learning Engineer at Wayve, we're looking for the following skills and experience. Essential * Extensive and proven track record of shipping deep ...

next page

Showing results 1-20

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

Google Machine Learning Engineer information

See Michigan salary details

$27.5K

$112.2K

$168.7K

How much do google machine learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for google machine learning engineer in Michigan is $112,234.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,500.00 and $135,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Google Machine Learning Engineer position, and why are they important?

To thrive as a Google Machine Learning Engineer, you need strong expertise in mathematics, statistics, programming (especially Python or C++), and a solid background in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms (like Google Cloud), and advanced certifications can be highly beneficial. Excellent problem-solving, teamwork, and communication skills help you collaborate across teams and explain complex models to stakeholders. These skills are essential to driving innovation, building scalable solutions, and ensuring impactful results in a fast-paced, research-driven environment.

What is a Google Machine Learning Engineer job?

A Google Machine Learning Engineer designs, builds, and optimizes machine learning models to improve Google's products and services. They work with large datasets, implement algorithms, and deploy scalable AI systems. Collaboration with data scientists, software engineers, and product teams is essential to integrate models into real-world applications. Strong knowledge of Python, TensorFlow, and cloud computing is often required. This role focuses on both research and practical implementation to enhance automation and decision-making across Google products.

What types of projects and collaborations can Google Machine Learning Engineers expect to be involved in?

Google Machine Learning Engineers often contribute to diverse projects, such as developing next-generation search algorithms, optimizing user experiences across products, or creating scalable machine learning systems for internal and external clients. The role frequently involves collaborating with data scientists, product managers, software engineers, and researchers to define project goals and deliver impactful solutions. You can expect to participate in code reviews, prototype new models, and provide expert input during technical discussions. This collaborative, interdisciplinary approach ensures innovative outcomes and offers ongoing opportunities for professional growth and skill development.

What are the most commonly searched types of Google Machine Learning Engineer jobs in Michigan? The most popular types of Google Machine Learning Engineer jobs in Michigan are:
What are popular job titles related to Google Machine Learning Engineer jobs in Michigan? For Google Machine Learning Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Google Machine Learning Engineer jobs in Michigan look for? The top searched job categories for Google Machine Learning Engineer jobs in Michigan are:
Google Machine Learning Engineer jobs near you
Machine Learning Engineering Senior Engineer

Machine Learning Engineering Senior Engineer

FastTek

Dearborn, MI • On-site

$96K - $131K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 29 days ago

Job description

Machine Learning Engineering Senior Engineer #1056751
Position Description:
  • ML Ops
  • Build scalable and robust ML data pipelines in the cloud to process large volumes of connected vehicle data to support our agentic initiatives.
  • Optimize existing ML solutions for performance, security, and cost-effectiveness
  • Utilize continual learning methods to continuously improve model performance Other
  • Develop exceptional analytical data products using both streaming and batch ingestion patterns on Google Cloud Platform with solid data warehouse principles.
  • Build data pipelines to monitoring quality of data and performance of analytical models and agentic solutions.
  • Maintain the infrastructure of the data platform using terraform and continuously develop, evaluate, and deliver code using CI/CD.
  • Collaborate with data analytics stakeholders to streamline the data acquisition, processing, and presentation process.
  • Implement an enterprise data governance model and actively promote the concept of data - protection, sharing, reuse, quality, and standards.
  • Enhance and maintain the DevOps capabilities of the data platform.
  • Continuously optimize and enhance existing data solutions (pipelines, products, infrastructure) for best performance, high security, low vulnerability, low costs, and high reliability.
  • Work in an agile product team to deliver code frequently using Test Driven Development (TDD), continuous integration and continuous deployment (CI/CD).
  • Promptly address code quality issues using SonarQube, Checkmarx, Fossa, and Cycode throughout the development lifecycle.
  • Perform any necessary data mapping, data lineage activities and document information flows.
  • Monitor the production pipelines and provide production support by addressing production issues as per SLAs.
  • Provide analysis of connected vehicle data to support new product developments and production vehicle improvements.
  • Provide visibility to data quality/vehicle/feature issues and work with the business owners to fix the issues.
  • Demonstrate technical knowledge and communication skills with the ability to advocate for well-designed solutions.
  • Continuously enhance your domain knowledge of connected vehicle data, connected services and algorithms/models/solutions developed by data scientists and AI engineers.
  • Stay current on the latest data engineering practices and contribute to the technical direction of the company while keeping a customer-centric approach.

Skills Required:
Technical Communication, Communications, Google Cloud Platform, TensorFlow, Data Governance, Machine Learning, Python, Artificial Intelligence & Expert Systems, GitHub, Tekton, Docker, Jira, Microservices, Data Architecture, Agile Software Development, SQL, Java, Spark, Cloud Architecture, Apache Kafka, REST APIs
  • Technical Communication - This person will need to describe clearly the ML/AI Ops needs and strategy to colleagues potentially up to executives across a wide cross section of people from very knowledge to not technically knowledgeable in this area.
  • Communications - In addition to the technical communication needed, this person will need to be a great communicator to work with people in other organizations who are stakeholders and we need to work together and not have there be communication gaps
  • Google Cloud Platform - Deep knowledge of how to implement ML / AI Ops in the GCP Platform specifically is required
  • TensorFlow
  • Data Governance - This role will need to implement an enterprise data governance model and actively promote the concept of data - protection, sharing, reuse, quality, and standards.
  • Machine Learning - We need an ML Ops expert
  • Python - Some of the ML Ops pipeline will likely need to be setup using this code
  • Artificial Intelligence & Expert Systems - The ML Ops pipeline needs to be set up for AI Agentic Solutions in mind as well.
  • GitHub - This is where our code will reside, so this is needed SEE 10 TO 21 IN ADDITION INFORMATION

Skills Preferred:
Telematics, Machine Learning, Data Modeling, Cloud Infrastructure, Data Mining, Database Design, Troubleshooting (Problem Solving), Labor Supervision
  • Telematics - Knowledge of this is nice, as some of our data will be Telematics data
  • Machine Learning
  • Data Modeling - In order to understand how the data will interact with the ML Operations.
  • Cloud Infrastructure
  • Data Mining
  • Database Design
  • Troubleshooting (Problem Solving)
  • Labor Supervision - Will need to mentor and advise junior team members to spread ML Ops expertise across the organization

Experience Required:
  • Master's degree or foreign equivalent degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field, and 4 years of experience OR equivalent combination of education and experience (6+ years with Bachelor's Degree).
  • 4 years of professional experience in:
    • Data engineering, data product development and software product launches
    • At least three of the following languages: Java, Python, Spark, Scala, SQL
  • 3 years of cloud data/software engineering experience building scalable, reliable, and cost-effective production batch and streaming data pipelines using:
    • Data warehouses like Amazon Redshift, Microsoft Azure Synapse Analytics, Google BigQuery. o Workflow orchestration tools like Airflow.
    • Relational Database Management System like MySQL, PostgreSQL, and SQL Server.
    • Real-Time data streaming platform like Apache Kafka, GCP Pub/Sub
    • Microservices architecture to deliver large-scale real-time data processing application.
    • REST APIs for compute, storage, operations, and security.
    • DevOps tools such as Tekton, GitHub Actions, Git, GitHub, Terraform, Docker.
    • Project management tools like Atlassian JIRA. Even better if you have...

Experience Preferred:
  • D. or foreign equivalent degree in Computer Science, Software Engineering, Information System, Data Engineering, or a related field.
  • 2 years of experience with ML Model Development and/or MLOps.
  • Committed code to improve open-source data/software engineering projects
  • Experience architecting cloud infrastructure and handling application migrations/upgrades.
  • GCP Professional Certifications.
  • Demonstrated passion to mine raw data and realize its hidden value.
  • Passion to experiment/implement state of the art data engineering methods/techniques.
  • Experience working in an implementation team from concept to operations, providing deep technical subject matter expertise for successful deployment.
  • Experience implementing methods for automation of all parts of the pipeline to minimize labor in development and production.
  • Analytics skills to profile data, troubleshoot data pipeline/product issues.
  • Ability to simplify, clearly communicate complex data/software ideas/problems and work with cross-functional teams and all levels of management independently.
  • Ability to mentor and advise junior team members

Education Required:
  • Bachelor's Degree

Education Preferred:
  • Master's Degree

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.