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Mlops Jobs in Rochester, MI (NOW HIRING)

SME

AI/ML and Data Engineer

Southfield, MI · On-site

$104K - $125K/yr

Establish and mature MLOps/LLMOps practices, including CI/CD, model and prompt versioning, monitoring/observability, rollback procedures, and cost/performance optimization for production environments.

Munich Re

Technical Architect - Data, Analytics & AI

Livonia, MI · Hybrid

$59.75 - $76.75/hr

  • Medical

  • Life

  • Retirement

  • PTO

Define and govern enterprise AI architecture standards , including model lifecycle management, MLOps, and AI platform integration. * Ensure responsible and compliant AI adoption, aligned with AI ...

Little Caesars

Applied AI Engineer

Detroit, MI

$113K - $136K/yr

... CD, MLOps, and responsible AI deliveryExperience with Databricks, notebooks, model serving, MLflow, and related cloud services such as Azure AI Foundry, Microsoft Fabric, or Azure Data Factory ...

Stellantis

ICT Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Exposure to MLOps concepts, model deployment, or monitoring * Hands-on experience with Palantir Foundry, Snowflake Intelligence * Master's degree in Data Science, Statistics, Engineering, Computer ...

company826

AI/ML and Data Engineer

Southfield, MI · On-site +1

$104K - $125K/yr

Establish and mature MLOps/LLMOps practices, including CI/CD, model and prompt versioning, monitoring/observability, rollback procedures, and cost/performance optimization for production environments.

Ilitch

Applied AI Engineer

Detroit, MI · On-site

Understanding of modern product and engineering practices such as Agile, DevOps, CI/CD,MLOps, and responsible AI delivery * Experience with Databricks, notebooks, model serving,MLflow, and related ...

Deloitte

Google AI Lead Architect

Detroit, MI · On-site

$54.75 - $75/hr

Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs/microservices, and CI/CD/MLOps/LLMOps with Vertex AI Pipelines and Cloud Build. * Lead cloud-native ...

Reply

Manager, Data Engineering

Detroit, MI

$160K - $190K/yr

Ability to create working environments for data engineers and scientists, and general knowledge of ML, AI, LLMs, and MLOps * Knowledge and familiarity with Microsoft Purview * DevOps for data, GitHub ...

Pwc

ERP AI Engineer - Manager

Detroit, MI

$99K - $232K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... MLOps tooling and CI/CD pipelines for ML - Experience with vector databases and semantic search architectures - Translating complex business problems into AI solution designs - Contributing to ...

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All JobsMlops JobsMlops Jobs in Rochester, MI

Mlops information

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

Is MLOps in demand?

MLOps is a rapidly growing field as organizations increasingly adopt machine learning models in production. Professionals with skills in cloud platforms, automation, and tools like Kubernetes and Docker are highly sought after, reflecting strong industry demand for MLOps expertise.

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

To thrive as an MLOps Engineer, you need a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What is MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.

What are popular job titles related to Mlops jobs in Rochester, MI?

For Mlops jobs in Rochester, MI, the most frequently searched job titles are:

What cities near Rochester, MI are hiring for Mlops jobs?

Cities near Rochester, MI with the most Mlops job openings:

Mlops jobs near you
Infographic showing various Mlops job openings in Rochester, MI as of August 2026, with employment types broken down into 88% Full Time, 6% Part Time, and 6% Contract. Highlights an 71% Physical, 10% Hybrid, and 19% Remote job distribution.

Sr. Cloud Engineer, SDV Platform, Engineering platform Group

Astemo

Farmington Hills, MI

$102K - $141K/yr

Full-time

Re-posted 15 days ago

Job description

Company Name:

ASTEMO AMERICAS, INC.

Job Family:

Engineering

Job Description:

Summary:

Astemo Americas, Inc. is looking for experienced cloud engineers with a Bachelor's/Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related engineering field to join our SDV Platform Software Group as a Sr. Cloud Engineer to design, implement, and operate a secure, scalable, automotive-grade cloud infrastructure platform enabling Software-Defined Vehicle (SDV) architecture, Over-the-Air (OTA) rollout, vehicle data services, and AI/ML lifecycle integration. The position works at the intersection of cloud platforms (AWS/Azure/GCP), edge/vehicle compute, DevSecOps & MLOps, and automotive cybersecurity & functional safety. The position requires the engineer to work as a team member with good communication and written skills.

Job Duties:

  • The candidate will work in close collaboration with Astemo teams in Japan and cross-functional engineering departments in the USA, including embedded ECU software teams, AI/ML engineering, cybersecurity organization, and cloud teams in Astemo Japan.
  • Design and architect multi-region, highly available cloud infrastructure for OTA backend services, vehicle identity & provisioning, fleet telemetry ingestion, remote diagnostics, and feature-on-demand services; define reference architectures for Cloud-to-Vehicle, Cloud-to-Edge gateway, and Cloud-to-Simulation/HPC communication.
  • Architect and operate a secure OTA campaign management platform, including update artifact storage & signing pipelines, phased rollout orchestration, rollback and safe-state mechanisms, and integration with ECU software version and vehicle configuration management systems; ensure compliance with ISO 24089 and UNECE R156.
  • Build and maintain DevSecOps CI/CD pipelines for backend microservices, OTA backend, and data pipelines, implementing artifact signing and container security scanning.
  • Ensure compliance with ISO 26262 (where cloud impacts safety), ISO/SAE 21434 cybersecurity, and global data privacy regulations, working with functional safety, cybersecurity, and legal/compliance organizations.
  • Support customer workshops, technical deep dives, and contribute to RFQ technical responses.

Qualifications:

  • 7-12 years of experience in cloud engineering is required.
  • Strong hands-on experience with AWS, Azure, or GCP, Kubernetes, Terraform, and REST/gRPC APIs is required.
  • Knowledge of PKI systems, HSM integration, and secure boot & firmware signing concepts is required.
  • Experience in designing and operating large-scale distributed systems is required.
  • Knowledge of OTA architecture, ECU software lifecycle, and AUTOSAR (Classic/Adaptive) is a strong plus.
  • Knowledge of vehicle network architecture is a plus.
  • Knowledge of automotive cybersecurity standards (e.g., ISO/SAE 21434) is a plus.
  • Candidates should exhibit skills in technical writing, and time and project management.

Education: Bachelor's/Master's degree in computer science, Computer Engineering, Electrical Engineering, or in a related engineering field. Preference will be given to Master's candidates.

Experience: Minimum of 7 years applicable experience in cloud engineering

Job level determined by various factors such as organization size, responsibility, career stage, and capabilities.

Supervisory Responsibilities: Leading, building and mentoring the efforts of engineers who are responsible for sub-project activities.

Working conditions:

Physical Demands: Required to sit or stand for long periods of time. The employee may occasionally lift and/or move up to 25 pounds.

Travel: Domestic and international may be required as needed.

Equal Opportunity Employer (EOE) - Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender, identity, disability, protected veteran status and national origin.

At Astemo, we're challenging the status quo with the power of diversity, inclusion, and collaboration. Our goal is to build an inclusive work environment that celebrates the differences of our employees. We want to ensure that every employee feels valued, respected and empowered. We don't just accept difference-we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products, and our community. Astemo is proud to be an equal opportunity employer.

If you need a reasonable accommodation to apply for a job at Astemo, please send the nature of the request and contact information to am-jobs@hitachiastemo.com when applying for the position.

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