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Machine Learning Ops Engineer Jobs (NOW HIRING)

University of Florida

OPS Engineer

Gainesville, FL · On-site

$35.92 - $40.71/hr

OPS Engineer Job no: 540809 Work type: Temp Full-Time Location: Main Campus (Gainesville, FL ... Strong understanding of the breadth of machine learning to include supervised, unsupervised ...

SwiftCruit

Senior Engineer, Data Science

Oklahoma City, OK · On-site

$150 - $190/hr

Job Summary The Senior Engineer, Data Science is a hands-on technical role who designs, builds, and ... Applies Machine Learning Ops best practices to automate training, testing, deployment, monitoring ...

Paradigm

WI · On-site

$120 - $180/hr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are ... Deploy and support machine learning models and AI solutions in production, maintaining best ...

4MindsAI Inc.

Machine Learning Operations Engineer

Dallas, TX

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Role Overview As Machine Learning Ops Engineer at 4Minds, you will own the infrastructure that makes our AI platform perform, scale, and ship across the most demanding deployment environments in the ...

New

Myparadigm

WI · On-site

$140 - $190/hr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are ... Deploy and support machine learning models and AI solutions in production, maintaining best ...

Paradigm

Senior ML Ops Engineer

Irving, TX · On-site

$140 - $200/hr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are ... Deploy and support machine learning models and AI solutions in production, maintaining best ...

Coca-Cola

Senior Manager, Machine Learning Ops

Atlanta, GA

$125K - $160K/yr

Engineering Best Practices: Write clean, modular, and testable code (primarily in Python) while ... A solid understanding of the machine learning lifecycle, containerized microservices architectures ...

Paradigm

Senior ML Ops Engineer

Seattle, WA · On-site

$123K - $170K/yr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are ... end-to-end machine learning lifecycle, including model training, deployment, monitoring, and ...

Paradigm

Senior ML Ops Engineer

Denver, CO · On-site

$123K - $170K/yr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are ... end-to-end machine learning lifecycle, including model training, deployment, monitoring, and ...

iHerb

Principal Machine Learning Engineer

California, MO · On-site

$205 - $230/hr

... Ops engineer, or related position). Education Requirements Bachelor's Degree in Computer Science, Electrical Engineering, or related field required; Master's Degree preferred. Judgment / Reasoning ...

WTS Paradigm LLC

Senior ML Ops Engineer

Irving, TX · On-site

$123K - $170K/yr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are ... end-to-end machine learning lifecycle, including model training, deployment, monitoring, and ...

Diverse Lynx

ML Ops Engineer

Cincinnati, OH · On-site

They are seeking an ML Ops Engineer to develop and deploy solutions using AWS technologies ... Machine Learning certification Company : Diverselynx IT Consulting Services Founded in 2002, the ...

Paradigm

Senior ML Ops Engineer

Middleton, WI · On-site

$123K - $170K/yr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are ... end-to-end machine learning lifecycle, including model training, deployment, monitoring, and ...

Paradigm

Senior ML Ops Engineer

Irving, TX · Remote

$123K - $170K/yr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are ... end-to-end machine learning lifecycle, including model training, deployment, monitoring, and ...

4MindsAI Inc.

Machine Learning Operations Engineer

Dallas, TX · On-site

$130 - $200/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Role Overview As Machine Learning Ops Engineer at 4Minds, you will own the infrastructure that makes our AI platform perform, scale, and ship across the most demanding deployment environments in the ...

New

Chalk

Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

They are seeking an Infrastructure Engineer to automate and manage their infrastructure ... Machine Learning Ops/Infrastructure Company : Chalk is a data platform for AI inference that ...

Raft

ML Ops Engineer

Tampa, FL · On-site

They are seeking an ML Ops Engineer to design, build, and maintain the infrastructure and pipelines for Machine Learning model training and deployment, collaborating with a cross-functional data team.

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Machine Learning Ops Engineer information

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How much do machine learning ops engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for machine learning ops engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is a machine learning ops engineer?

A Machine Learning Ops Engineer (MLOps Engineer) focuses on deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and software engineering, ensuring models run efficiently, reliably, and at scale. Their responsibilities include automating workflows, managing infrastructure, and ensuring CI/CD pipelines for ML models. They work with tools like Kubernetes, Docker, and cloud platforms to streamline model deployment. Ultimately, an MLOps Engineer ensures that machine learning models are operationalized and continuously improved in a real-world environment.

What does a machine learning ops engineer do?

A typical day for a Machine Learning Ops Engineer involves collaborating with data scientists to streamline the deployment of models, building and maintaining scalable infrastructure on cloud services, and automating workflows with CI/CD tools. You may troubleshoot issues in production environments, monitor model performance, and implement solutions for model versioning and retraining. Often, you’ll work closely with software engineers, DevOps teams, and data analysts to ensure seamless integration of machine learning solutions into products. This cross-functional role keeps you engaged with cutting-edge technology and provides opportunities to influence both technical and business outcomes.

What skills and qualifications are needed to be a machine learning ops engineer?

To thrive as a Machine Learning Ops Engineer, you need a solid grasp of machine learning concepts, cloud platforms, software engineering, and DevOps practices, typically supported by a degree in computer science or a related field. Experience with tools like Docker, Kubernetes, TensorFlow, CI/CD pipelines, and certifications such as AWS Certified Machine Learning – Specialty are highly valuable. Strong problem-solving skills, communication, and the ability to work collaboratively across data science and engineering teams set top candidates apart. These skills ensure reliable deployment, scalability, and optimization of machine learning models in production environments.

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Machine Learning Ops Engineer jobs near you
Infographic showing various Machine Learning Ops Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning (ML) Ops Engineer - IS Clinical Research - Full Time 8 Hour Days (Exempt) (Non-Unio

Keck Medicine of USC

Los Angeles, CA • On-site

Full-time

Re-posted 12 days ago

Keck Medicine of USC rating

7.5

Company rating: 7.5 out of 10

Based on 54 frontline employees who took The Breakroom Quiz

299th of 1,059 rated hospitals

Job description

Job Summary:
Keck Medicine of USC is seeking a Machine Learning (ML) Ops Engineer to manage the full lifecycle of machine learning models. The role involves collaborating with data scientists and clinical operations to implement AI solutions that enhance patient care and operational excellence.
Responsibilities:
• Design, build and maintain production-grade machine learning models, with real-time inference, scalability, and reliability.
• Develop end-to-end scalable ML infrastructure using cloud platforms, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.
• Develop AI pipelines for various data processing needs, including data ingestion, pre-processing, and search and retrieval, ensuring solutions meet all technical and business requirements.
• Monitor model performance for data drift and concept drift detection, automate retraining processes where necessary to maintain model accuracy and relevance.
• Collaborate with data scientists, data engineers, analytics teams, and DevOps teams to design and implement robust deployment pipelines for continuous improvement of machine learning models.
• Implement and optimize CI/CD pipelines for machine learning models, automating testing and deployment processes.
• Configure and manage monitoring and logging solutions to track model performance, system health, and anomalies, enabling timely intervention and proactive maintenance.
• Implement version control systems for machine learning models, parameters, results and associated code to track changes and facilitate collaboration.
• Ensure all machine learning systems meet security and compliance standards, including data protection and privacy regulations.
• Lead engineering efforts in creating and implementing methods and workflows for ML/GenAI model engineering, LLM advancements, and optimizing deployment frameworks while aligning with business strategic directions.
• Maintain clear and comprehensive documentation of MLOps processes and configuration.
• Strong communication and collaboration skills, to collaborate cross-functionally and align on deployment strategies and technical requirements
• Other duties as assigned.
Qualifications:
Required:
• Bachelor’s Degree in computer science, engineering or closely related field
• Proven experience with: Artificial intelligence and machine learning platforms (e.g., AWS, Azure or GCP)
• Containerization technologies (e.g., Docker) or container orchestration platforms (e.g., Kubernetes)
• CI/CD tools (e.g., Github Actions)
• Programming languages and frameworks (e.g., Python, R, SQL)
• MLOps engineering principles, agile methodologies, and DevOps lifecycle management
• Technical writing and documentation for AI/ML models and processes
• Healthcare data and machine learning use cases
• Ability to solve complex problems through troubleshooting
• Deep understanding of coding, architecture, and deployment processes
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Excellent organizational skills and attention to detail
• Self-starter with the ability to solution when requirements are vague or ambiguous
• Fire Life Safety Training (LA City) If no card upon hire, one must be obtained within 30 days of hire and maintained by renewal before expiration date (Required within LA City only)
Preferred:
• Master’s degree in computer science, engineering or closely related field
Company:
Keck Medicine of USC is a Healthcare Center. Founded in 2009, the company is headquartered in Los Angeles, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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