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Mlops Engineer Jobs (NOW HIRING)

Redolent, Inc.

MLOps Engineer

Sunnyvale, CA · On-site

MLOps Engineer Duration: 12+ Months Location:Sunnyvale CA - hybrid Rate: DOE Key Responsibilities : Design and implement scalable model serving platforms for both batch and real-time inference Build ...

Stefanini

MLOps Engineer

Dearborn, MI · On-site

Stefanini is looking for a MLOps Engineer (Dearborn, MI) For quick apply, please reach out to Navneet Pathak at / We are seeking an experienced AI Engineer to design, develop, and deploy intelligent ...

AgileEngine

MLOps Engineer ID72409

Dallas, TX · On-site

They are seeking a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment while collaborating closely with data scientists ...

Hirekeyz Inc

MLOps Engineer

San Francisco, CA · On-site

Role: MLOps Engineer Location: San Francisco, California Duration: Long Term Contract Key Responsibilities * Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.

Booz Allen Hamilton

MLOps Engineer, Mid

Chantilly, VA

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and help build a system that will have a positive impact in the intelligence community (IC)? What if you ...

IT America Inc

DevOps/MLOps Engineer

Cumming, GA · On-site

$47 - $64.50/hr

... MLOps Engineer Location: Cumming, GA Duration: Long-term contract Note: Final interview will take place onsite--only local candidates will be considered * Our Fintech client is looking for an ...

Tror AI for everyone

MLOPS Engineer

Concord, CA · On-site

Job Role: MLOPS Engineer Job Location: Concord, CA (100% Onsite) Job Type: Contract Key Responsibilities: * Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.

NBCUniversal

Staff MLOps Engineer

They are seeking a Staff MLOps Engineer to build and scale infrastructure for large media datasets, ensuring automated, reproducible, and performant data pipelines for the machine learning lifecycle.

Booz Allen Hamilton

MLOps Engineer, Mid

Alexandria, VA

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and help build a system that will have a positive impact in the intelligence community (IC)? What if you ...

Booz Allen Hamilton

MLOps Engineer, Mid

Aurora, CO

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and help build a system that will have a positive impact in the intelligence community (IC)? What if you ...

Booz Allen Hamilton

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 difference and help build a system that will have a positive impact in the intelligence community (IC)

Apptronik

Staff MLOps Engineer

Austin, TX · On-site

JOB SUMMARY Apptronik is seeking a Staff MLOps Engineer to own the technical direction of our MLOps platform - the system of record for datasets, experiments, model artifacts, and serving paths that ...

Apple

Machine Learning (MLOps) Engineer

Cupertino, CA · On-site

As an MLOps Engineer, you will be the backbone of our machine learning infrastructure, ensuring that AI/ML systems are reliable, scalable, and continuously improving in production. You will bridge ...

Booz Allen Hamilton, Inc.

MLOps Engineer, Mid

Chantilly, VA · On-site

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and help build a system that will have a positive impact in the intelligence community (IC)? What if you ...

HCA Healthcare

Staff MLOps Engineer

Nashville, TN · On-site

Staff ML Ops Engineer Job Summary and Qualifications Position Summary The Staff MLOps Engineer plays a pivotal role in shaping our MLOps practice within ITG by building and enhancing a scalable ...

HCA Healthcare

Staff MLOps Engineer

Franklin, TN · On-site

Staff ML Ops Engineer Job Summary and Qualifications Position Summary The Staff MLOps Engineer plays a pivotal role in shaping our MLOps practice within ITG by building and enhancing a scalable ...

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Mlops Engineer information

Are MLOps engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning and AI 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.

What is an MLOps Engineer job?

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and operations by automating workflows, optimizing infrastructure, and ensuring model reliability. Their role includes CI/CD for ML models, data pipeline management, and performance monitoring. They also work with cloud platforms, containerization, and orchestration tools to scale ML systems efficiently.

What engineers make $300,000 a year?

Senior MLOps engineers with extensive experience, advanced skills in machine learning deployment, cloud platforms, and automation tools can earn $300,000 or more annually. High compensation is often associated with specialized expertise, leadership roles, and working in competitive tech environments.

What engineers make $500,000?

Senior-level engineers in specialized fields such as software engineering, data engineering, and MLOps engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and leadership roles. Compensation often includes base salary, bonuses, and stock options, particularly in high-growth tech companies.

What are some common challenges Mlops Engineers face in their daily work?

Mlops Engineers often encounter challenges in integrating new machine learning models into existing production systems while ensuring minimal downtime and maintaining data integrity. Managing the scaling and orchestration of models across various cloud or on-prem environments can be complex, requiring close coordination with data scientists and DevOps teams. Staying up to date with rapidly evolving tools and best practices is also essential in this field. Addressing these challenges provides valuable opportunities to innovate and improve both technical processes and team collaboration.

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

To thrive as an Mlops Engineer, you need strong skills in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science, engineering, or a related field. Familiarity with tools such as Docker, Kubernetes, TensorFlow, AWS/GCP/Azure, and CI/CD systems is essential, and certifications like AWS Certified Machine Learning or Kubernetes Administrator are often valued. Effective communication, problem-solving, and teamwork are crucial soft skills for collaborating across data science and IT teams. These abilities enable Mlops Engineers to efficiently deploy, manage, and scale machine learning models in dynamic production environments.

What does an MLOps engineer do?

An MLOps engineer is responsible for deploying, managing, and maintaining machine learning models in production environments. They work with tools like Docker, Kubernetes, and cloud platforms to automate workflows, ensure model reliability, and monitor performance. Their role combines software engineering, data science, and DevOps practices to streamline the deployment and lifecycle management of machine learning systems.
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Mlops Engineer jobs near you
Infographic showing various Mlops Engineer job openings in the United States as of July 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

MLOps Engineer

Quality IT Source, LLC

Milpitas, CA • On-site

Other

This job post has expired 2 days ago. Applications are no longer accepted.

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

Apply