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Senior Mlops Engineer Jobs (NOW HIRING)

Zoolatech

Senior MLOps Engineer Central Europe

Central, LA · On-site

$125 - $150/hr

We are collaborating with a leading European Online Fashion & Beauty Retailer to find a highly capable and self-driven Machine Learning Engineer (MLE/MLOps Focus) to join a fast-moving and impactful ...

Zoolatech

$125 - $150/hr

We are collaborating with a leading European Online Fashion & Beauty Retailer to find a highly capable and self-driven Machine Learning Engineer (MLE/MLOps Focus) to join a fast-moving and impactful ...

Conch Technologies Inc

MLOps Engineer

Dallas, TX · On-site

MLOps Engineer Location: Grapevine, TX & Dallas, TX - (Hybrid) Duration: 6+ Months Contract Key ... With Regards, Chanakya | Sr. IT Recruiter Desk: 901-313-3066 Email: chanakya@conchtech.com LinkedIn ...

AgileEngine, LLC.

MLOps Engineer ID72409

Houston, TX · On-site

$150 - $200/hr

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine, LLC.

MLOps Engineer ID72409

Jacksonville, TX · On-site

$150 - $200/hr

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine

MLOps Engineer ID72409

Austin, TX · On-site

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine, LLC.

MLOps Engineer ID72409

Orlando, FL · On-site

$125 - $150/hr

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine

MLOps Engineer ID72409

Tallahassee, FL · On-site

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine, LLC.

MLOps Engineer ID72409

Miami, FL · On-site

$150 - $200/hr

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine, LLC.

MLOps Engineer ID72409

Blacksburg, VA · On-site

$150 - $200/hr

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine

MLOps Engineer ID72409

West Palm Beach, FL · On-site

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine

MLOps Engineer ID72409

Orlando, FL · On-site

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine, LLC.

MLOps Engineer ID72409

Tampa, FL · On-site

$125 - $150/hr

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine, LLC.

MLOps Engineer ID72409

Baltimore, MD · On-site

$150 - $200/hr

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine

MLOps Engineer ID72409

Fort Lauderdale, FL · On-site

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

AgileEngine

MLOps Engineer ID72409

Miami, FL · On-site

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the ...

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Senior Mlops Engineer information

See salary details

$59.5K

$126.6K

$183.5K

How much do senior mlops engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for senior mlops engineer in the United States is $126,557.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $143,500.00 per year, depending on experience, location, and employer.

What is a senior MLOps engineer?

A Senior MLOps Engineer is an experienced professional who bridges the gap between data science, machine learning, and software engineering. They are responsible for designing, deploying, and maintaining scalable machine learning systems in production environments. Their role involves automating workflows, monitoring model performance, ensuring reproducibility, and managing the infrastructure needed to support machine learning operations. Senior MLOps Engineers also collaborate with data scientists, software developers, and IT teams to ensure smooth integration and continuous delivery of ML models. They play a crucial role in making machine learning solutions reliable, efficient, and scalable for business applications.

What are the key skills and qualifications needed to thrive as a senior MLOps engineer?

To thrive as a Senior MLOps Engineer, you need deep expertise in machine learning workflows, software engineering, and cloud infrastructure, typically supported by a degree in computer science or related fields. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and platforms such as AWS, GCP, or Azure, as well as certifications in cloud or DevOps, are highly valuable. Strong problem-solving, collaboration, and communication skills set standout professionals apart in this role. These skills and qualities are crucial to ensuring robust, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges senior MLOps engineers face when deploying machine learning models to production environments?

Senior MLOps Engineers often encounter challenges such as managing model versioning, ensuring reproducibility, and scaling deployments across diverse infrastructure. Balancing the needs of data scientists for experimentation with the stability and reliability requirements of production systems can be complex. Additionally, integrating continuous integration and continuous deployment (CI/CD) pipelines for ML workflows and monitoring model performance post-deployment are ongoing responsibilities. Collaboration with data scientists, software engineers, and IT operations is crucial to address these challenges and maintain robust, efficient ML systems.

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

AspectSenior Mlops EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with ML deployment toolsBachelor's/Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in productionFocus on data analysis, model development, and insights generation
Industry UsageUsed in tech, finance, healthcare for ML deploymentUsed across industries for data analysis and modeling

The main difference is that Senior Mlops Engineers specialize in deploying and maintaining machine learning models in production environments, while Data Scientists focus on developing models and analyzing data. Both roles require strong technical skills, but their day-to-day tasks and focus areas differ significantly.

Are senior MLOps engineers in demand?

Senior MLOps engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are valued for their expertise in deploying, managing, and scaling machine learning models using tools like Kubernetes, Docker, and cloud platforms. The role often requires strong skills in automation, CI/CD pipelines, and cloud infrastructure, making experienced professionals highly sought after.

How much do senior MLOps engineers make?

Senior MLOps engineers typically earn between $120,000 and $180,000 annually, depending on experience, location, and company size. They often have expertise in cloud platforms, automation tools, and machine learning deployment pipelines, which can influence salary levels.
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Senior Mlops Engineer jobs near you
Infographic showing various Senior Mlops Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 92% Full Time, 3% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.

Senior MLOps Engineer Central Europe

Central, LA • On-site

Zoolatech
Software Development • 201 - 500 employees
Learn more about Zoolatechexternal

$125 - $150/hr

Other

Posted 19 days ago

Job description

Are you passionate about improving the way Machine Learning systems are developed, deployed, and scaled in real-world production environments? We are collaborating with a leading European Online Fashion & Beauty Retailer to find a highly capable and self-driven Machine Learning Engineer (MLE/MLOps Focus) to join a fast-moving and impactful team.

This role is centered around building robust ML workflows, streamlining feature creation, and standardizing ML components to ensure scalability, consistency, and speed across the organization. You’ll work at the intersection of engineering and data science, playing a key part in shaping how machine learning is delivered at scale.

Design and build ML platform components supporting data access, feature management, model training, deployment, and inference in production environments.

Develop infrastructure and tooling that enable ML practitioners to experiment, version, deploy, and monitor models in a reliable and automated way.

Build and improve scalable, reusable ML components and workflows that help teams efficiently develop and deploy models.

Contribute to standardizing ML workflows — from feature creation to model rollout to ensure consistency and reliability across teams.

Build and maintain observability and reliability tooling for ML systems, including model health checks and automated retraining processes.

Establish best practices, frameworks, and reference implementations that raise the bar for engineering rigor and speed in ML delivery.

Work closely with infrastructure, data, and security teams to ensure that ML systems are secure, compliant, and production-grade by default.

5+ years of experience in Machine Learning Engineering or MLOps roles

Strong hands-on experience with Airflow (MWAA), MLFlow, and/or SageMaker

Familiarity with ML observability tools such as Grafana, custom metric logging, model drift detection, and alerting mechanisms

Proficiency in building CI/CD pipelines for ML systems with automated testing and validation

Understanding of secure and compliant deployment of ML pipelines

Excellent debugging and problem-solving skills

Experience with OpenAI API usage in production, containerization, and Kubernetes orchestration is highly valued

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