ZipRecruiter

Log In

1

Mlops Machine Learning Engineer Jobs (NOW HIRING)

LotusLynx

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$97K - $134K/yr

Please note: 2 openings-one SR MLOps Engineer and one Lead MLOps Engineer. Both roles are direct ... The ideal candidate will bring hands-on experience supporting machine learning solutions in ...

New

RAPID EAGLE INC

Machine Learning Engineer

Sunnyvale, CA · Remote

$70 - $80/hr

Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine Learning Engineer to ... Monitor model performance, retrain models, and implement MLOps best practices. * Work with large ...

RAPID EAGLE INC

Machine Learning Engineer

Sunnyvale, CA · Remote

$70 - $80/hr

Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine Learning Engineer to ... Monitor model performance, retrain models, and implement MLOps best practices. * Work with large ...

RAPID EAGLE INC

Machine Learning Engineer

Sunnyvale, CA · Remote

$70 - $80/hr

Health insurance Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine ... Monitor model performance, retrain models, and implement MLOps best practices. * Work with large ...

Prosum Inc.

Machine Learning Engineer

CA · On-site

$75 - $89/hr

This position requires strong experience in MLOps, DevOps practices, and cloud-based AI infrastructure. Key Responsibilities * Design, build, deploy, and maintain machine learning models in ...

Rapid Eagle Inc

Machine Learning Engineer

$70 - $80/hr

Health insurance Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine ... Monitor model performance, retrain models, and implement MLOps best practices. * Work with large ...

Compunnel

Machine Learning Engineer

Plano, TX · On-site

Develop and maintain Python-based machine learning models, feature engineering processes, and MLOps ... automation solutions. * Build and optimize SQL transformations, views, and ELT pipelines to support ...

Darwill, Inc.

Machine Learning Engineer

Villa Park, IL · On-site

MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING) Overview Darwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Qualifications: * 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role. * Proven experience deploying and maintaining machine learning models in production at scale.

ICONMA

Machine Learning Engineer

Mclean, VA

Machine Learning Engineer Our client, a financial company, is looking for a Machine Learning ... Python, AWS, Kubernetes, Kubeflow, MLOps, ML Tooling - Spark, Pandas, Numpy * Good to have: Data ...

Ai Squared

Machine Learning Engineer

Washington, DC

Qualifications: * 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role. * Proven experience deploying and maintaining machine learning models in production at scale.

AI Squared

Machine Learning Engineer

Washington, DC

Qualifications: * 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role. * Proven experience deploying and maintaining machine learning models in production at scale.

AI Squared

Machine Learning Engineer

Washington, DC

Qualifications: * 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role. * Proven experience deploying and maintaining machine learning models in production at scale.

next page

Showing results 1-20

All JobsMlops Machine Learning Engineer Jobs

Mlops Machine Learning Engineer information

See salary details

$31.5K

$128.8K

$193.5K

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

As of Jun 16, 2026, the average yearly pay for mlops machine learning 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.

Is MLOps harder than DevOps?

MLOps, as a specialized subset of DevOps focused on deploying and maintaining machine learning models, often involves additional challenges such as data management, model versioning, and monitoring. While both require skills in automation, scripting, and cloud environments, MLOps typically demands expertise in machine learning workflows and tools like TensorFlow or PyTorch, making it more complex in certain aspects compared to traditional DevOps.

What does an MLOps Machine Learning Engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

How does an MLOps Machine Learning Engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning models in various industries. Their skills in deploying, managing, and scaling machine learning systems, along with knowledge of tools like Docker, Kubernetes, and cloud platforms, make them valuable in the job market.

What engineers make $500,000?

Senior machine learning engineers, including those specializing in MLOps, often reach or exceed $500,000 annually with experience, advanced skills, and in high-demand industries like tech or finance. Compensation can include base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

How much do MLOps engineers make?

MLOps engineers typically earn between $100,000 and $150,000 annually, with salaries increasing based on experience, location, and expertise in tools like Kubernetes, Docker, and cloud platforms. Senior roles or those with specialized skills can exceed $180,000 per year.

What are the key skills and qualifications needed to thrive as an MLOps Machine Learning Engineer, and why are they important?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.
More about Mlops Machine Learning Engineer jobs
What cities are hiring for Mlops Machine Learning Engineer jobs? Cities with the most Mlops Machine Learning Engineer job openings:
What states have the most Mlops Machine Learning Engineer jobs? States with the most job openings for Mlops Machine Learning Engineer jobs include:
What job categories do people searching Mlops Machine Learning Engineer jobs look for? The top searched job categories for Mlops Machine Learning Engineer jobs are:
Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops Machine Learning Engineer job openings in the United States as of June 2026, with employment types broken down into 50% Full Time, and 50% Temporary. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer - LLM / MLOps

HRC Global Services

Reston, VA • On-site

Full-time

Posted 4 hours ago

Job description

Machine Learning Engineer – LLM / MLOps

Job Title: Machine Learning Engineer – LLM & MLOps
Location: Remote (U.S.)
Employment Type: Full-Time

About the Opportunity:
An exciting role for an ML Engineer to build scalable ML systems, deploy models, and work with cutting-edge AI technologies including LLMs and RAG architectures.

Key Responsibilities:

  • Build, train, and deploy ML models at scale
  • Develop reusable pipelines using Databricks and MLflow
  • Implement CI/CD workflows for ML deployment
  • Work with LLMs, RAG, and AI agent frameworks
  • Monitor model performance, drift, and retraining cycles

Required Skills:

  • 5+ years of ML Engineering experience
  • Strong Python programming and ML frameworks (PyTorch, TensorFlow, Scikit-learn)
  • Hands-on experience with Databricks, MLflow, PySpark
  • Experience with AWS (S3, SageMaker, Lambda, etc.)
  • Strong understanding of MLOps and model lifecycle

Preferred:

  • Experience building AI-driven applications (Streamlit, Gradio)
  • Strong system design and data pipeline experience
  • Business understanding of AI applications

Clearance: Public Trust (or eligible)

Hashtags:
#MLEngineer #MachineLearning #MLOps #LLM #AWS #Databricks #PySpark #AIEngineering #RemoteJobs #HiringNow