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Manager Mlops Engineer Jobs (NOW HIRING)

Model deployment, monitoring, and lifecycle management * Kubernetes, Docker, Infrastructure as Code ... Standardize MLOps and LLMOps workflows across teams * Build and optimize CI/CD pipelines for ML and ...

... system reliability; • Manage experiment tracking and model versioning to ensure full ... in MLOps, DevOps, Data Engineering, Machine Learning, or Software Engineering • Degree in ...

THE ROLE Senior Engineering Manager, MLOps We are seeking a Senior Engineering Manager, MLOps to join our growing team. The ideal candidate is a technical visionary with a proven track record of ...

Stefanini is looking for a MLOps Engineer (Dearborn, MI) For quick apply, please reach out to ... management. Ensure AI solutions are reliable, scalable, secure, and optimized for production ...

MLOps Engineer Location: San Francisco, California Duration: Long Term Contract Key ... Implement CI/CD workflows for model lifecycle management, including versioning, monitoring, and ...

MLops Engineer Location: Plano, TX Duration: Long Term About CTC: Founded in 1996, CTC is a global ... Manage SageMaker Model Registry -- cross-account model promotion, versioning, immutability, and ...

MLOps Engineer

$185K - $200K/yr

The Role We're looking for an MLOps Engineer to build and operate the platform that gets our ... Contribute to and manage containerized workloads on Kubernetes and codify infrastructure with ...

Job Role: MLOPS Engineer Job Location: Concord, CA (100% Onsite) Job Type: Contract Key ... Implement CI/CD workflows for model lifecycle management, including versioning, monitoring, and ...

Deploy and manage systems for monitoring model performance and data drift in production ... MLOps Engineer in a fast-paced environment in applied machine learning. • Prior experience in ...

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... Experience with leveraging MLOps platforms and Machine Learning (ML) CI/CD workflows to manage ...

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... Experience with leveraging MLOps platforms and Machine Learning (ML) CI/CD workflows to manage ...

DevOps/MLOps Engineer

Cumming, GA · On-site

$47 - $64.50/hr

Our Fintech client is looking for an experienced DevOps / MLOps Engineer to help build and manage cloud infrastructure, deployment pipelines, and operational systems supporting AI-driven platform ...

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... Experience with leveraging MLOps platforms and Machine Learning (ML) CI/CD workflows to manage ...

Mid MLOps Engineer

Chantilly, VA · On-site

$77K - $176K/yr

R0241240 MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a ... Experience with leveraging MLOps platforms and Machine Learning (ML) CI/CD workflows to manage ...

... versioning, while managing cloud environments and GPU compute resources for cost-effective ... MLOps , DevOps , Data Engineering , Machine Learning , or Software Engineering ; - Degree in ...

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Manager Mlops Engineer information

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How much do manager mlops engineer jobs pay per hour?

As of Jun 29, 2026, the average hourly pay for manager mlops engineer in the United States is $55.99, according to ZipRecruiter salary data. Most workers in this role earn between $40.14 and $74.52 per hour, depending on experience, location, and employer.

What is the difference between Manager Mlops Engineer vs Data Scientist?

AspectManager Mlops EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with MLOps toolsDegree in Data Science, Statistics, or related; proficiency in programming and analytics
Work EnvironmentCollaborates with engineering and operations teams to deploy ML modelsAnalyzes data, builds models, and interprets results for business insights
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsCommon across tech, marketing, research for data analysis and modeling

The Manager Mlops Engineer focuses on deploying and maintaining machine learning models in production environments, overseeing MLOps pipelines. In contrast, Data Scientists primarily analyze data and develop models for insights. Both roles require technical skills but differ in their focus on deployment versus analysis.

More about Manager Mlops Engineer jobs
What cities are hiring for Manager Mlops Engineer jobs? Cities with the most Manager Mlops Engineer job openings:
What are the most commonly searched types of Mlops Engineer jobs? The most popular types of Mlops Engineer jobs are:
What states have the most Manager Mlops Engineer jobs? States with the most job openings for Manager Mlops Engineer jobs include:
Infographic showing various Manager Mlops Engineer job openings in the United States as of June 2026, with employment types broken down into 2% Internship, 35% Full Time, 59% Contract, and 4% Nights. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution, with an average salary of $116,463 per year, or $56 per hour.

Other

Posted 10 days ago


Key responsibilities

  • Standardize MLOps and LLMOps workflows across teams.

  • Build and optimize CI/CD pipelines for ML and GenAI applications.

  • Deploy, monitor, and manage models in production environments.


Job description

Key Skills:

  • Strong hands-on experience with Databricks and MLflow
  • Experience building and maintaining MLOps/LLMOps platforms
  • Cloud expertise in Azure and/or Google Cloud Platform
  • CI/CD pipeline development and automation
  • Model deployment, monitoring, and lifecycle management
  • Kubernetes, Docker, Infrastructure as Code (Terraform preferred)
  • Experience supporting GenAI/LLM applications in production
  • Knowledge of model evaluation, observability, governance, and release management

Responsibilities:

  • Standardize MLOps and LLMOps workflows across teams
  • Build and optimize CI/CD pipelines for ML and GenAI applications
  • Deploy, monitor, and manage models in production environments
  • Establish best practices for MLflow, model governance, and operational excellence
  • Collaborate with data science, platform, and engineering teams