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Machine Learning Ops Engineer Jobs (NOW HIRING)

RELX Group plc

Senior ML Ops Engineer

Philadelphia, PA · On-site

$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 ...

RELX

Senior ML Ops Engineer

Philadelphia, PA · On-site

$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 ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA · On-site

$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 ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Machine Learning/AI Engineer Location: Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and ... Knowledge of Machine Learning Ops and CI/CD tools for automation of build, test, and deploy models ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Machine Learning/AI Engineer Location: Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and ... Knowledge of Machine Learning Ops and CI/CD tools for automation of build, test, and deploy models ...

Elsevier

Senior ML Ops Engineer

$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 ...

RELX

Senior ML Ops Engineer

$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 ...

LMI

ML Ops Engineer - Clearance Required

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 ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Machine Learning/AI Engineer Location: Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and ... Knowledge of Machine Learning Ops and CI/CD tools for automation of build, test, and deploy models ...

LMI

ML Ops Engineer - Clearance Required

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 ...

LMI Government Consulting

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 ...

Conch Technologies

ML OPS Engineer

Concord, CA · On-site

ML OPS Engineer Location: Concord, CA ( 5 days a week onsite ) Duration: 12+ Months Contract Job ... ready machine learning platforms across cloud and on-premises environments. The ideal candidate ...

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IMR Soft LLC

ML Ops Engineer

Concord, CA · On-site

ML Ops Engineer Concord, CA 12 months contract Job Summary We are seeking an experienced ML Ops Engineer to design, build, and support scalable, secure, and production-ready machine learning ...

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All JobsMachine Learning Ops Engineer Jobs

Machine Learning OPS Engineer information

See salary details

$31.5K

$128.8K

$193.5K

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

As of Sep 10, 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.

Are machine learning ops engineers in demand?

Machine Learning Ops Engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Kubernetes and TensorFlow. The role is expected to grow as organizations prioritize AI-driven solutions and infrastructure automation.
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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 September 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 100% In-person job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Ops Data Engineer

Southlake, TX • On-site

Charles Schwab Inc.
See more jobs at Charles Schwab Inc.external

$102K - $185K/yr

Full-time

Re-posted 18 days ago

Job description

Your Opportunity
At Schwab, you're empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us "challenge the status quo" and transform the finance industry together.
We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).
Hands-on technical lead responsible for taking AI/ML projects from development to production in Google Cloud Platform (GCP). This role owns architecture, implementation, deployment, and operations.
Required Skills
  • Expert-level Google Cloud experience, especially services used for AI/ML use cases (e.g., BigQuery, Vertex AI, GCS, Dataflow, Pub/Sub, Cloud Run/GKE, Composer/Airflow, IAM, Cloud Monitoring/Logging)
  • Expert Python for production-grade data and backend engineering
  • Strong SQL and data modeling for analytics, scalability, and operational workloads
  • Strong CI/CD and containerization skills (Docker, Git workflows, automated testing, release pipelines)
  • Solid cloud security and governance practices (IAM, secrets, least privilege, auditability)
  • Strong observability and reliability engineering skills (monitoring, alerting, incident response, SLAs/SLOs)
  • Fundamental understanding of AI/ML lifecycle/model development needed to productionize AI/ML systems (training/serving integration, model versioning, pipeline monitoring support)

What you have
Required Work Experience
  • 8+ years in data/software engineering, including 2+ years in technical leadership
  • Proven track record delivering production grade AI/ML use cases on GCP or other cloud providers
  • Experience building and operating scalable batch/streaming pipelines
  • Experience leading design reviews, enforcing engineering standards, and mentoring data engineers
  • Demonstrated support of critical systems in production
  • Experience partnering with data scientists/MLE/Ops teams to deliver business outcomes

Core Responsibilities
  • Design and build production-ready AI/ML powered, security related use cases on GCP
  • Lead end-to-end deployment from prototype to production with clear quality gates
  • Understand, document, and lead the resolution of technical debts
  • Implement coding standards, test strategy, data quality checks, alerting mechanisms, and operational runbooks
  • Ensure platform reliability, security, and cost efficiency
  • Mentor the MLOps and data engineers while remaining hands-on in code and delivery

Apply