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Full Time Mlops Jobs (NOW HIRING)

Booz Allen Hamilton

MLOps Engineer, Mid

Aurora, CO · On-site

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton

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 ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

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 ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton

MLOps Engineer, Mid

Alexandria, VA · On-site

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Niyam IT, Inc.

DevOps/MLOps Engineer

Ashburn, VA · On-site

$54 - $74/hr

Niyam is seeking a DevOps/MLOps Engineer to join our team in support of our work with a federal ... This full-time position will be hybrid to Ashburn, VA. This position is contingent upon award of ...

Niyam IT, Inc.

DevOps/MLOps Engineer

Ashburn, VA · On-site +1

$54 - $74/hr

Niyam is seeking a DevOps/MLOps Engineer to join our team in support of our work with a federal ... This full-time position will be hybrid to Ashburn, VA. This position is contingent upon award of ...

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Full Time Mlops information

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How much do full time mlops jobs pay per hour?

As of Jul 6, 2026, the average hourly pay for full time mlops in the United States is $17.50, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $18.99 per hour, depending on experience, location, and employer.

What are Full Time MLOps roles?

Full Time MLOps roles focus on building, deploying, and maintaining machine learning models in production environments on a full-time basis. MLOps professionals bridge the gap between data science and IT operations, ensuring that machine learning workflows are reliable, scalable, and automated. Their responsibilities often include managing model versioning, monitoring performance, automating pipelines, and collaborating with both data scientists and engineers. This role is essential for organizations seeking to operationalize AI solutions and maintain them effectively over time.

What are the key skills and qualifications needed to thrive as a Full Time MLOps Engineer, and why are they important?

To thrive as a Full Time MLOps Engineer, you need a solid background in machine learning, software engineering, and cloud computing, often supported by a degree in computer science or a related field. Experience with tools like Docker, Kubernetes, CI/CD pipelines, and cloud platforms (AWS, Azure, GCP), as well as familiarity with version control systems and infrastructure-as-code, is essential. Strong problem-solving, collaboration, and communication skills help you bridge the gap between data science and IT operations teams. These skills ensure the efficient deployment, scalability, and maintenance of machine learning models in production environments.

What are the most common challenges faced by Full Time MLOps professionals in maintaining production machine learning systems?

Full Time MLOps professionals often encounter challenges like ensuring seamless model deployment, managing version control for both code and data, and monitoring model performance in production environments. They must also address issues related to scalability, reproducibility, and automating workflows to reduce manual intervention. Collaborating closely with data scientists, engineers, and IT teams is essential to troubleshoot issues promptly and implement best practices for continuous integration and delivery.

What is the difference between Full Time Mlops vs Data Engineer?

AspectFull Time MlopsData Engineer
Required CredentialsCertifications in ML, cloud platforms, scriptingCertifications in data warehousing, SQL, cloud platforms
Work EnvironmentCollaborates with data scientists, DevOps teamsWorks with data pipelines, databases, ETL processes
Industry UsageAI/ML projects, deployment pipelinesData infrastructure, data pipeline development

Full Time Mlops roles focus on deploying and maintaining machine learning models in production, requiring knowledge of ML frameworks and cloud services. Data Engineers build and manage data pipelines and infrastructure. While both roles involve working with data and cloud platforms, Full Time Mlops emphasizes ML deployment and automation, whereas Data Engineers concentrate on data architecture and processing.

More about Full Time Mlops jobs
What cities are hiring for Full Time Mlops jobs? Cities with the most Full Time Mlops job openings:
What are the most commonly searched types of Mlops jobs? The most popular types of Mlops jobs are:
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What job categories do people searching Full Time Mlops jobs look for? The top searched job categories for Full Time Mlops jobs are:
Full Time Mlops jobs near you
Infographic showing various Full Time Mlops job openings in the United States as of June 2026, with employment types broken down into 17% As Needed, and 83% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution, with an average salary of $36,392 per year, or $17.5 per hour.

Machine Learning Engineer - LLM / MLOps

HRC Global Services

Reston, VA • On-site

Full-time

Posted 20 days ago

Job description

Machine Learning Engineer – LLM / MLOps

Job Title: Machine Learning Engineer – LLM & MLOps
Location: Remote (U.S.)
Employment Type: Full-Time

About the Opportunity:
An exciting role for an ML Engineer to build scalable ML systems, deploy models, and work with cutting-edge AI technologies including LLMs and RAG architectures.

Key Responsibilities:

  • Build, train, and deploy ML models at scale
  • Develop reusable pipelines using Databricks and MLflow
  • Implement CI/CD workflows for ML deployment
  • Work with LLMs, RAG, and AI agent frameworks
  • Monitor model performance, drift, and retraining cycles

Required Skills:

  • 5+ years of ML Engineering experience
  • Strong Python programming and ML frameworks (PyTorch, TensorFlow, Scikit-learn)
  • Hands-on experience with Databricks, MLflow, PySpark
  • Experience with AWS (S3, SageMaker, Lambda, etc.)
  • Strong understanding of MLOps and model lifecycle

Preferred:

  • Experience building AI-driven applications (Streamlit, Gradio)
  • Strong system design and data pipeline experience
  • Business understanding of AI applications

Clearance: Public Trust (or eligible)

Hashtags:
#MLEngineer #MachineLearning #MLOps #LLM #AWS #Databricks #PySpark #AIEngineering #RemoteJobs #HiringNow