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Machine Learning Ops Engineer Jobs (NOW HIRING)

Keylent Inc

ML Ops Engineer

Berkeley Heights, NJ

Machine Learning Ops Engineer to build & support scalable, highly available and robust Machine Learning (Client) /Deep Learning (DL) platform using Client/DL frameworks, High-Performance Computing ...

Moody's Analytics

MLOps Engineer

New York, NY · On-site +1

As the Machine Learning Ops Engineer for the AI Team you will: * Work closely with the Data Science team and the Data Engineers and DevOps teams in order to deploy machine learning models.

Lorven Technologies

ML Ops Engineer

Concord, CA · On-site

ML Ops Engineer Concord CA Contract Cleint Round - Inperson Overview Tachyon Cortex Machine Learning AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions. Key ...

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Machine Learning Ops Engineer information

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$31.5K

$128.8K

$193.5K

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

As of Jun 11, 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 job?

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 typical day look like for a Machine Learning Ops Engineer?

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 are the key skills and qualifications needed to thrive in the Machine Learning Ops Engineer position, and why are they important?

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 June 2026, with employment types broken down into 6% Internship, 88% Full Time, 3% Contract, and 3% Nights. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Ops Engineer

Hatch Global Search

Middletown, NJ

Other

Posted 8 days ago

Job description

ML Ops Engineers

Our client is a growing software company. Several key positions have opened because of this expansion including Machine Learning Ops Engineers at Senior and Principal levels with machine learning experience. These are hybrid positions in Monmouth County. If you have solid computer science fundamentals (data structures, algorithms, etc.) and experience with C or Python and Linux you may qualify for one of these exceptional opportunities.

The ML Ops Engineer roles involve deploying, managing, and optimizing machine learning systems and pipelines, with a focus on ransomware acquisition and analysis operations. Key responsibilities include managing cloud services, data pipelines, and system administration tasks while collaborating with cross-functional teams to ensure seamless integration of ML models. Proficiency in Python, shell scripting, VMware administration, and data analysis is essential. Strong problem-solving, communication, and teamwork skills, along with experience in ML model deployment and pipeline management, are critical for success in this role. Full job description is available.

Requirements include: BS, MS or PhD in CS, CE, EE, Math, or other technical discipline; Machine Learning Ops knowledge; a few years of software development; team player with great interpersonal skills; desire to contribute and learn.

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