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Mlops Machine Learning Engineer Jobs in Michigan

May Mobility

Lead Machine Learning Engineer

Ann Arbor, MI · On-site

$100K - $132K/yr

They are seeking a Lead Machine Learning Engineer to enhance their Machine Learning capabilities for autonomous vehicles, focusing on designing and evaluating state-of-the-art models and leading ...

Bespoke Labs

Machine Learning Engineer

Kalamazoo, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Detroit, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Lansing, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Warren, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Flint, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Allendale, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Crowe LLP

Machine Learning Engineer

Grand Rapids, MI

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

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Mlops Machine Learning Engineer information

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

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

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

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

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

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

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

Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops 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.

Lead Machine Learning Engineer

May Mobility

Ann Arbor, MI • On-site

$100K - $132K/yr

Full-time

Re-posted 23 days ago

Job description

Job Summary:
May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. They are seeking a Lead Machine Learning Engineer to enhance their Machine Learning capabilities for autonomous vehicles, focusing on designing and evaluating state-of-the-art models and leading small teams of engineers.
Responsibilities:
• Design, train and evaluate state of the art models for May's autonomous driving, simulation and ML Platform stack.
• Leverage emerging techniques in the End-to-End driving, Vision Language Action (VLA), World or Foundation model domains to solve commercial-scale problems.
• Lead small teams of cross functional Engineers beyond the state of the art.
• Define data balance, training experiment and evaluation practices to train efficiently at petabyte scale.
Qualifications:
Required:
• Extensive practical experience in one of the following domains: Vision Language Action Models, Generative World Models, Foundation Models in Robotics, Data Centric AI
• A minimum of 4 years of industry experience working on commercial robotics systems.
• A minimum of 1 year mentoring ML Engineers in a commercial or lab environment.
• Master's degree in Robotics, Computer Science, or Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation.
• Practical experience handling the 'Long Tail' problem in Machine Learning.
• Strong programming skills in Python/PyTorch in a Linux environment.
• Functional understanding of LiDAR, Camera and Radar processing techniques.
Preferred:
• PhD and/or published research in the described specialty domains.
• Familiar with common post-training techniques.
• Experience deploying models to resource constrained and edge hardware
• Functional understanding of C/C++/CUDA memory and threading models.
Company:
May Mobility is a manufacturing firm that designs and develops autonomous technology vehicles for self-driving transportation solutions. Founded in 2017, the company is headquartered in Ann Arbor, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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