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Mlops Data Engineer Jobs (NOW HIRING)

Sierra Nevada Corporation

MLOps & Data Engineer

Englewood, CO · On-site

$113K - $136K/yr

As a Data Engineer II, you will oversee the development and optimization of complex data pipelines and transformations. You will collaborate with cross-functional teams to ensure the efficient and ...

Tiger Analytics Inc.

MLOps Lead Engineer

Saint Louis, MO

$99K - $131K/yr

Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations. * Core Technical Stack: Advanced ...

Tiger Analytics

MLOps Lead Engineer

Saint Louis, MO · On-site

$97K - $128K/yr

Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations. * Core Technical Stack: Advanced ...

Tiger Analytics

$75K - $99K/yr

Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations. * Core Technical Stack: Advanced ...

Tiger Analytics Inc.

MLOps Lead Engineer

Saint Louis, MO · On-site

$99K - $131K/yr

Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations. * Core Technical Stack: Advanced ...

Tiger Analytics Inc.

MLOps Lead Engineer

Saint Louis, MO · On-site

$99K - $131K/yr

Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations. * Core Technical Stack: Advanced ...

Qualis1 Inc

Data Engineer : Hybrid Role

Washington, DC · On-site

$129K - $155K/yr

Role: Data Engineer Location: Washington, DC, (Hybrid) Duration: 6+ months Description ... Experience working with cloud databases such as AlloyDB, CloudSQL, Big Query Experience with MLOps ...

Syntricate Technologies

Data Engineer/MLOps

Irving, TX · On-site

$106K - $127K/yr

Syntricate Technologies is seeking a Data Engineer with expertise in MLOps. The role involves building data pipelines and working with various tools in the Hadoop ecosystem, as well as collaborating ...

Central Strategies, LLC

AI/ML Data Engineer

Washington, DC · On-site

$129K - $155K/yr

... MLOps, data governance, workflow modernization, and reliable delivery of mission-ready data ... Engineer reusable data services and curated data products for predictive analytics, generative AI ...

Central Strategies, LLC

$84K - $101K/yr

... MLOps, data governance, workflow modernization, and reliable delivery of mission-ready data ... Engineer reusable data services and curated data products for predictive analytics, generative AI ...

Syntricate Technologies

Data Engineer with MLOps

Irving, TX · On-site

$106K - $127K/yr

Job Summary : Syntricate Technologies is seeking a Data Engineer with MLOps expertise based in Irving, TX. The role involves building data pipelines, working with various data tools, and ...

Whisker

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Develops and supports MLOps workflows, including model tracking, versioning, and lifecycle management using MLflow * Builds and maintains CI/CD pipelines for both data engineering and machine ...

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How much do mlops data engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for mlops data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

What are the key skills and qualifications needed to thrive as an MLOps data engineer?

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

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

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.
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Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

MLOps Data Pipeline Engineer (Airflow & MLflow) - Q125

Alpharetta, GA • On-site

R2 Technologies Corporation
See more jobs at R2 Technologies Corporationexternal

$111K - $134K/yr

Full-time

Medical, Retirement, PTO

Re-posted 8 days ago

Job description

Overview:
R2 Technologies Corporation (R2), headquartered in Alpharetta, GA, is a leading IT services provider specializing in Java, .NET, Big Data, Cloud Computing (AWS, GCP, Azure), Artificial Intelligence (AI), Machine Learning (ML), software development, project management, SAP, and enterprise resource planning (ERP). We empower clients-from startups to Fortune 1000 companies-with scalable, platform-based solutions and data-driven insights using modern cloud technologies. Our commitment to blending highly skilled talent with innovative productivity platforms ensures rapid delivery of business value, making us one of the most respected and trusted technology companies in the United States. At R2, we're passionate about driving operational excellence and competitive advantage for our clients through cutting-edge AI, ML, and cloud solutions. Join our team and help shape the future of technology innovation!
MLOps Data Pipeline Engineer (Airflow & MLflow)
Location: Alpharetta, GA (willing to travel to client locations)
Employment Type: Full-Time (W2)
Role Overview
We are seeking a skilled MLOps Data Pipeline Engineer to build and manage machine learning pipelines using Airflow and MLflow. This role focuses on integrating Spark or Python-based data workflows for efficient model training and deployment.
Key Responsibilities
  • Design and implement machine learning pipelines using Airflow for orchestration and MLflow for model management.
  • Develop data workflows with Spark or Python to preprocess and feed data into ML models.
  • Automate MLOps processes for model training, validation, and deployment using Kubeflow or similar tools.
  • Collaborate with data scientists to monitor and optimize ML pipeline performance and accuracy.
  • Ensure data pipeline scalability, reliability, and governance in production environments.
  • Troubleshoot and resolve issues in data workflows to maintain seamless ML operations.

Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
  • 3 years of experience as a Data Engineer with a focus on MLOps and machine learning pipelines.
  • Proficiency in using Airflow for pipeline orchestration and MLflow for model lifecycle management.
  • Experience with Spark or Python for building scalable data workflows in ML environments.
  • Strong understanding of MLOps practices and their integration into data engineering pipelines.

Preferred Qualifications
  • Familiarity with Kubeflow for advanced MLOps workflows and Kubernetes-based deployments.
  • Exposure to cloud platforms like AWS or GCP for hosting MLOps pipelines.
  • Knowledge of data versioning tools like DVC for managing ML datasets and models.

Compensation & Benefits
  • Competitive salary and comprehensive benefits package (healthcare, PTO, 401k).
  • Opportunities for professional growth and upskilling in AI and cloud technologies.

R2 Technologies Corporation is an equal opportunity employer and values diversity in the workplace.
Skills:
Data Engineer, MLOps, Airflow, MLflow, Kubeflow, Spark, Python, Machine Learning Pipelines

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