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Mlops Data Engineer Jobs in Washington, DC (NOW HIRING)

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 ...

Central Strategies, LLC

AI/ML Data Engineer

Washington, DC · On-site

$150 - $200/hr

... 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 ...

Accenture Federal Services

Data Engineer

Suitland, MD · On-site

$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 ...

Berkley

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 ...

Accenture Federal Services

Data Engineer

Suitland, MD · On-site

$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 ...

Accenture Federal Services

Data Engineer

Suitland, MD · On-site

$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 ...

Steampunk

MLOps Engineer

Mclean, VA · On-site

$115K - $150K/yr

The MLOps Engineer works closely with Data Scientists, AI Developers, Data Engineers, and cloud engineering teams to streamline model deployment, monitoring, and lifecycle management in alignment ...

Steampunk

MLOps Engineer

Mclean, VA · On-site

$115K - $150K/yr

The MLOps Engineer works closely with Data Scientists, AI Developers, Data Engineers, and cloud engineering teams to streamline model deployment, monitoring, and lifecycle management in alignment ...

Steampunk

MLOps Engineer

Mclean, VA · On-site

$115K - $150K/yr

The MLOps Engineer works closely with Data Scientists, AI Developers, Data Engineers, and cloud engineering teams to streamline model deployment, monitoring, and lifecycle management in alignment ...

Oteemo Inc.

Sr. Data Engineer

Reston, VA · On-site

$110K - $149K/yr

We're looking for a Senior Data Engineer to design and implement AI features end to end -- from ... Implement MLOps/LLMOps practices -- CI/CD for data workflows, automated agent evaluation, and ...

Accenture Federal Services

Data Engineer

Suitland, MD · On-site

$123K - $148K/yr

They are seeking a skilled Data Engineer to design, build, and maintain data infrastructure ... MLOps tools (e.g., Amazon SageMaker, MLflow, or Kubeflow) in production environments. • Strong ...

Karsun Solutions, LLC

Senior AI Data Engineer

Herndon, VA · On-site

$165K - $180K/yr

MLOps Operationalization: Set up, establish, and operationalize MLOps practices directly within the ... AI/Data Engineering: 5+ years of proven experience building large-scale data platforms, with at ...

Expression Networks

Data Engineer

Arlington, VA · On-site

$150 - $200/hr

The Data Engineer will work as part of a multidisciplinary team integrating data engineering ... Familiarity with MLOps, API development, and secure cloud-based environments, including AWS, Azure ...

Expression

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

The Data Engineer will work as part of a multidisciplinary team integrating data engineering ... Familiarity with MLOps, API development, and secure cloud-based environments, including AWS, Azure ...

Expression

Data Engineer

Arlington, VA

$131K - $158K/yr

The Data Engineer will work as part of a multidisciplinary team integrating data engineering ... Familiarity with MLOps, API development, and secure cloud-based environments, including AWS, Azure ...

Expression Networks

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

The Data Engineer will work as part of a multidisciplinary team integrating data engineering ... Familiarity with MLOps, API development, and secure cloud-based environments, including AWS, Azure ...

Staffed4U

Data Engineer

Chantilly, VA · On-site

$118K - $142K/yr

Data Engineer Location: Chantilly, VA Work Schedule: Full-Time, Onsite Clearance Required: Active ... Understanding of machine learning workflows and MLOps concepts. * Experience integrating and ...

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Showing results 1-20

All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Washington, DC

Mlops Data Engineer information

See Washington, DC salary details

$50.4K

$146.9K

$201K

How much do mlops data engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for mlops data engineer in Washington, DC is $146,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,700.00 and $155,700.00 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.

What are popular job titles related to Mlops Data Engineer jobs in Washington, DC?

For Mlops Data Engineer jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Mlops Data Engineer jobs in Washington, DC look for?

The top searched job categories for Mlops Data Engineer jobs in Washington, DC are:

Mlops Data Engineer jobs near you

Data Engineer : Hybrid Role

Qualis1 Inc

Washington, DC • On-site

$129K - $155K/yr

Contractor

Re-posted 24 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