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Mlops Data Engineer Jobs (NOW HIRING)

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 ...

Data Engineer

Princeton, NJ · On-site

$100K - $120K/yr

Data Engineer CURE Auto Insurance is a leading direct writer of auto insurance in New Jersey ... Exposure to MLOps/data needs for fraud detection, pricing, or claims severity models is a plus.

Senior Cloud Data Engineer

Tampa, FL · Remote

$108K - $147K/yr

Lead Cloud Data Engineer FLSA STATUS: Exempt EMPLOYMENT TYPE: Full-Time JOB PURPOSE: This role at ... Work with data scientists and AI specialists to automate model deployment lifecycles (MLOps). Data ...

Data Engineer

Suitland, MD

$123K - $148K/yr

Data Engineer We are looking for a skilled and passionate Data Engineer to join our team. You will ... ML Integration / MLOps : Support the implementation, deployment, and scaling of machine learning ...

Data Engineer

Manhattan, NY · Remote

$105K - $115K/yr

MLOps Integration: Collaborate with Data Scientists to implement automated CI/CD pipelines for ... ML Engineering: Familiarity with ML frameworks (PyTorch, TensorFlow) and MLOps tools (MLflow ...

Senior Cloud Data Engineer

Tampa, FL · Remote

$100K - $136K/yr

Lead Cloud Data Engineer FLSA STATUS: Exempt EMPLOYMENT TYPE: Full-Time JOB PURPOSE: This role at ... Work with data scientists and AI specialists to automate model deployment lifecycles (MLOps). Data ...

Data Engineer

Newington, CT

$114K - $137K/yr

In alignment with current industry?s best practices, this role integrates advanced data engineering, software development, and machine learning operations (MLOps) to deliver secure, scalable, and ...

Data Engineer

Newington, CT

$114K - $136K/yr

In alignment with current industrys best practices, this role integrates advanced data engineering, software development, and machine learning operations (MLOps) to deliver secure, scalable, and high ...

Databricks Data Engineer

Manassas, VA · On-site

$114K - $137K/yr

MLOps & ML-Enabled Data Pipelines * Partner with data scientists and data engineers to create feature pipelines, model training pipelines, and production scoring pipelines. * Deploy and ...

Data Engineer

Redstone Arsenal, AL · On-site

$116K - $140K/yr

Overview SOS International LLC (SOSi) is seeking Data Engineers to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government ...

Databricks Data Engineer

Manassas, VA · On-site

$114K - $137K/yr

MLOps & ML-Enabled Data Pipelines * Partner with data scientists and data engineers to create feature pipelines, model training pipelines, and production scoring pipelines. * Deploy and ...

Databricks Data Engineer

Manassas, VA

$114K - $137K/yr

MLOps & ML-Enabled Data Pipelines * Partner with data scientists and data engineers to create feature pipelines, model training pipelines, and production scoring pipelines. * Deploy and ...

Erwartungsmanagement Anforderungen Mehrjahrige Erfahrung als MLOps Engineer, ML Engineer oder Data ... Engineer Sehr gute Kenntnisse in Kubernetes-/OpenShift-basierten Umgebungen Erfahrung mit ML ...

Data Engineer

Redstone Arsenal, AL

$116K - $140K/yr

Overview SOS International LLC (SOSi) is seeking Data Engineers to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government ...

Data Engineer

Newington, CT · On-site

$114K - $137K/yr

In alignment with current industry's best practices, this role integrates advanced data engineering, software development, and machine learning operations (MLOps) to deliver secure, scalable, and ...

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Mlops Data Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do mlops data engineer jobs pay per year?

As of Jul 12, 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 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 engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects as organizations prioritize operationalizing AI solutions.

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

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 are MLOps Data Engineers?

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 is the salary of data engineer in MLOps?

The salary of an MLOps Data Engineer typically ranges from $90,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in cloud platforms, automation, and machine learning tools tend to earn higher salaries.

What engineer makes 500,000 a year?

Highly experienced senior MLOps Data Engineers with specialized skills in cloud platforms, automation, and large-scale data processing can earn salaries approaching or exceeding $500,000 annually, especially in competitive tech hubs or large organizations. Such roles often require advanced certifications, extensive experience, and expertise in tools like Kubernetes, Docker, and cloud services like AWS or Azure.

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.
More about Mlops Data Engineer jobs
What cities are hiring for Mlops Data Engineer jobs? Cities with the most Mlops Data Engineer job openings:
What states have the most Mlops Data Engineer jobs? States with the most job openings for Mlops Data Engineer jobs include:
Infographic showing various Mlops Data Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Engineer : Hybrid Role

Qualis1 Inc

Washington, DC • On-site

$129K - $155K/yr

Contractor

Re-posted 26 days ago


Job description

Role: Data Engineer

Location: Washington, DC, (Hybrid)

Duration: 6+ months

Description:

Responsibilities

  • Function as the lead Google data team point of contact to support NOTAM data platform
  • Be highly collaborative and work closely with data producers and data consumers, to understand the data needs, provide consultation, and align data solutions.
  • Lead database administration best practices including backup and recovery, performance tuning, scaling, data archival, database design and provide implementation support.
  • Create and deliver best practices, recommendations, sample code, and technical presentations, adapting to different levels of key business and technical stakeholders.
  • Analyze on-premise and cloud database environments, consulting on the optimal design for performance and deployment on Google Cloud Platform. Support the design, development, and maintenance of RDBMS, data warehouse and data pipeline solutions.

Must-Have Qualifications

  • Bachelor's degree in Computer Science or equivalent practical experience.
  • 5 years of experience with relational database technologies such as PostgreSQL, MySQL, SQL Server, or Oracle.
  • Experience working with business stakeholders to understand requirements, provide technical leadership, and educate teams on GCP best practices.

 Preferred Skillset Requirement

  • Experience with database management tools for backups, recovery, snapshot management, sharding, partitioning and database performance tuning.
  • Experience working with cloud databases such as AlloyDB, CloudSQL, Big Query Experience with MLOps, data warehousing, and data pipeline development, including ETL and ELT, dataflow, cloud functions.
  • Experience with application development.
  • Experience in database administration techniques including storage, clustering, availability, disaster recovery, security, logging, performance tuning, monitoring and auditing.
  • Experience developing, deploying, and managing machine learning models, including experience writing software in one or more languages, such as Java, Python, Golang