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Full Time Mlops Jobs (NOW HIRING)

Lockheed Martin

$128K - $225K/yr

The Space AI Talent Center is seeking a highly skilled Software/MLOps Engineer to join a cross ... Represented full time employees accrue 6.67 hours of Vacation per month; accrue up to 52 hours of ...

TriOptus LLC

Machine Learning Engineer

Atlanta, GA · On-site

$85.92 - $130/hr

* Senior MLOps Engineer (Contractor) About the Role: * Client is seeking an experienced Senior MLOps ... This contract position has potential to transition into a full-time role in the future based on ...

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How much do full time mlops jobs pay per hour?

As of Jun 16, 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 jobs pay $500,000 a year in the US?

High-paying roles in fields like executive management, investment banking, and specialized medical professions can reach or exceed $500,000 annually. In the tech industry, senior positions such as Chief Data Officers or highly experienced Machine Learning Engineers with advanced skills and certifications may also earn this level of compensation, especially with bonuses and stock options included.

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 engineer makes $500,000 a year?

Senior machine learning operations (MLOps) engineers with extensive experience, advanced skills in cloud platforms, automation, and deployment often earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living regions or within large tech companies. Such roles typically require strong expertise in software engineering, data pipelines, and machine learning frameworks, along with leadership responsibilities. Compensation varies based on location, company size, and individual expertise.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI executives, often found in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data engineering, along with significant experience and sometimes leadership responsibilities.

What jobs make $10,000 a month without a degree?

Full-time MLOps roles typically require specialized skills in machine learning, cloud platforms, and DevOps tools, and they often pay between $8,000 and $15,000 per month depending on experience. High-paying jobs without a degree in tech fields may include software engineering, sales, or entrepreneurship, but these often require relevant skills, certifications, or experience. Achieving $10,000 monthly income without a degree generally involves gaining expertise through self-education, certifications, or extensive experience in high-demand areas.

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.

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Full Time Mlops jobs near you

AI Engineer - GenAI, MLOps & Cloud Platforms - AIRLHV

NavitasPartners

Chandler, AZ • On-site, Remote

$55 - $73.25/hr

Full-time

Posted 19 days ago

Job description

AI Engineer – GenAI, MLOps & Cloud Platforms

Location: US / Canada (Remote/Hybrid)
Type: Contract / Full-Time

Overview:

Join a high-impact team delivering enterprise AI solutions. This role emphasizes building intelligent systems using modern ML, GenAI, and cloud-native technologies.

Key Responsibilities:

  • Develop and operationalize machine learning and GenAI models
  • Build scalable data and model pipelines using cloud technologies
  • Partner with cross-functional teams to deliver AI-driven insights
  • Ensure scalability, performance, and governance of AI systems

Required Skills:

  • Hands-on experience in ML engineering, MLOps, and model lifecycle management
  • Strong programming skills in Python and ML frameworks
  • Experience with cloud ecosystems (AWS, Azure, GCP)
  • Knowledge of distributed data processing and integration

Nice to Have / Coverage:

  • Experience with Databricks, Snowflake, or BigQuery for data engineering workflows
  • Familiarity with LangChain and agent-based AI systems
  • Exposure to enterprise AI governance and compliance standards
  • Experience collaborating with cloud/data platform architects

For more details reach at resumes@navitassols.com.