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Machine Learning Ops Engineer Jobs (NOW HIRING)

CIM Group

Sr. Machine Learning Ops Engineer

Los Angeles, CA · On-site

$140K - $179K/yr

They are seeking a Senior Machine Learning Ops Engineer to lead the design and maintenance of scalable infrastructure for ML model deployment and lifecycle management, with a focus on productionizing ...

CIM Group

Sr. Machine Learning Ops Engineer

Los Angeles, CA · On-site

$112K - $154K/yr

CIM Group is a community-focused real estate and infrastructure company seeking a Senior ML Ops Engineer to lead the design and maintenance of scalable infrastructure for ML model deployment and ...

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 ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Donato Technologies, Inc

ML Ops Engineer

Charlotte, NC · On-site

$60/hr

Overview Machine Learning AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions. Key Responsibilities * Develop and maintain ML pipelines using tools like MLflow ...

Logistics Management Institute

Overview LMI is seeking a Machine Learning Operations Engineer (ML Ops Engineer) to support the development of cutting-edge AI/ML solutions in collaboration with the Army's AI2C organization. This ...

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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 Jul 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 July 2026, with employment types broken down into 95% Full Time, 2% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.
Machine Learning Ops Engineer

Machine Learning Ops Engineer

Ruri Software Technologies LLC

Remote

$54 - $74/hr

Full-time

Posted 23 days ago

Job description

Job Title:- Machine Learning Ops Engineer
Duration:- 8+ months
Location:- Remote
Description
  • Proven expertise in machine learning model lifecycleProven expertise and experience in creating data pipelines using Python or R required for real-time model inferenceProven expertise and experience in creating a microservice using Flask or FastAPI or R equivalent for a machine learning model.
  • Experience with APIGEE is a must. Proven experience with Linux bash scripting, Python scripting, or Groovy scripting Proven experience with Docker, and KubernetesProven experience with MPP databases like Teradata and reasonable experience with Hadoop ecosystem products like Hive, HDFS, HBASE, etc.
  • Proven experience with streaming technologies like KafkaProven experience with CICD tools like Jenkins, Shell Scripting, Gitlab, Github, Gitlab Pages, and Gitlab Documentation Proven experience with logging, alerting, debugging, and monitoring tools like ELK, Kibana, Catchpoint, Prometheus, and Splunk. Experience with EKS, or GKE is a plus

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