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Mlops Data Engineer Jobs in Virginia (NOW HIRING)

Edgesource

Data Engineer

Centreville, VA · On-site +1

$113K - $136K/yr

Client is seeking a data engineer to grow our team performing cutting edge client work in mission ... Understanding of machine learning workflows and MLOps concepts. Working at Edgesource: As an ISO ...

M9 Solutions

Data Engineer

Springfield, VA · On-site

$60K - $180K/yr

M9 Solutions is seeking a Data Engineer to work onsite in support of a government contract for a ... Familiarity with MLOps tools or platforms (e.g., SageMaker, MLflow). GH 932 Full-Time Employee ...

M9 Solutions

Data Engineer

Springfield, VA · On-site

$60K - $180K/yr

M9 Solutions is seeking a Data Engineer to work onsite in support of a government contract for a ... Familiarity with MLOps tools or platforms (e.g., SageMaker, MLflow). GH 932 Full-Time Employee ...

Satsyil Corporation

Senior Data Engineer

Vienna, VA · On-site

$106K - $144K/yr

The Senior Data Engineer at Satsyil Corp will be responsible for designing, implementing, and ... Architect feature stores, MLOps pipelines with MLflow, and analytical data models optimized for BI ...

Entarian

MLOps Engineer

Arlington, VA · On-site

The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Data Drift Detection : Implement drift detection pipelines using tools like Evidently AI or Alibi ...

Entarian

MLOps Engineer

Arlington, VA · On-site

The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Data Drift Detection : Implement drift detection pipelines using tools like Evidently AI or Alibi ...

Entarian

MLOps Engineer

Arlington, VA · On-site

The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Data Drift Detection : Implement drift detection pipelines using tools like Evidently AI or Alibi ...

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Mlops Data Engineer information

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 Virginia?

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

What job categories do people searching Mlops Data Engineer jobs in Virginia look for?

The top searched job categories for Mlops Data Engineer jobs in Virginia are:

What cities in Virginia are hiring for Mlops Data Engineer jobs?

Cities in Virginia with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Data Engineer

Edgesource

Centreville, VA • On-site, Remote

$113K - $136K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 16 hours ago

Key responsibilities

  • Design, develop, and maintain ETL/ELT pipelines for batch and real-time processing using Python and SQL.

  • Integrate data from multiple sources, including databases, APIs, streaming platforms, PDFs, and MS Office files.

  • Build scalable data architectures to support analytics and machine learning workloads.

Job description

Company Overview:

For over 25 years, Edgesource Corporation has served as an innovative technology service provider for the Department of Defense (DOD), Department of Homeland Security (DHS), Department of State (DOS), the U.S. Intelligence Community, Law Enforcement, and other federal, state, and commercial clients locally, nationally, and abroad. From providing boutique technical solutions in support of the DOD Counter Unmanned Aerial Systems (CUAS) mission set to addressing the most critical Cybersecurity threats facing our nation as a prime contractor with the DHS Cybersecurity & Infrastructure Security Agency (CISA), a career at Edgesource is an opportunity to do meaningful, interesting, and impactful work.

Position Overview:

  • Client is seeking a data engineer to grow our team performing cutting edge client work in mission space. With overwhelming amounts of large data, client is seeking a data engineer to support data structuring for implementation into a larger enterprise system that is being custom developed for client.

Development is performed on client site.

Responsibilities:

  • Design, develop, and maintain ETL/ELT pipelines for batch and real-time processing using Python and SQL.
  • Integrate data from multiple sources, including databases, APIs, streaming platforms, PDFs, and MS Office files.
  • Build scalable data architectures to support analytics and machine learning workloads.
  • Optimize data processing and queries for performance and cost efficiency in AWS S3.
  • Exposure to PySpark or other big data frameworks is a plus for future pipeline scalability.
  • Develop and implement web scraping and data ingestion workflows to collect open-source data, integrating content and producing structured datasets and visualizations for analytics and stakeholder consumption.

Data Management & Optimization

  • Collect, clean, and validate large volumes of structured and unstructured data.
  • Track data versions, implement data quality checks, and ensure data reliability.
  • Design and optimize data storage in AWS S3, including raw, intermediate, and final datasets.
  • Implement data governance practices, including documentation, cataloging, lineage, and security.
  • Ensure compliance security standards.

Collaboration with Data Science & Stakeholders

  • Work closely with Data Scientists, Analysts, and stakeholders to understand data requirements.
  • Prepare clean, structured, and feature-ready datasets for analytics and machine learning.
  • Support feature engineering, aggregations, and transformations at scale.
  • Assist in deploying ML models to production, ensuring monitoring, versioning, and performance optimization.

APIs, Containers & CI/CD

  • Integrate with REST APIs.
  • Utilize Docker, Kubernetes, Git, and CI/CD pipelines to deploy and manage workflows.

Documentation & Communication

  • Document pipelines, data schemas, and transformations clearly.
  • Communicate technical concepts effectively with cross-functional teams.
  • Participate in code reviews and promote best practices across the team.

Required Qualifications:

  • 3–5 years + of professional experience in data engineering or related roles.
  • Strong collaboration skills to work effectively with Data Scientists, Analysts, and Engineering teams.
  • Ability to communicate complex technical concepts to non-technical stakeholders.
  • Detail-oriented, curious, and committed to data quality.
  • Capable of managing multiple priorities in a fast-paced environment.

Technical Skills

  • Python, SQL, and PySpark (highly desired) for data processing and pipeline development.
  • Elastic/OpenSearch for search and analytics solutions.
  • Experience with AWS cloud services and Linux environments.
  • Git for version control and collaborative development.
  • Understanding of machine learning workflows and MLOps concepts.

Working at Edgesource:
As an ISO 9001:2015 certified and CMMI Level 3 appraised small business, Edgesource specializes in providing a variety of technical solutions to include software development, database services, enterprise networking, data center virtualization, and management support. We are always seeking top-talent to join our team in helping to address the most critical technical challenges facing our nation.

At Edgesource, we understand that our employees are our greatest asset, and as such we offer a wide array of benefits to support the well-being of our staff to include:

- Flexible PTO Policy + 11 Paid Holidays -
- Flexible Work Schedules (Remote / Hybrid) -
- Medical / Dental / Vision / Flexible Spending Account (FSA) -
- 401k Plan with Match -
- Tuition & Professional Development Support -
- Commuter Benefits -
- Bonus & Employee Referral Programs -
- Career Growth Opportunities -

Disclaimer:

Edgesource Corporation is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. Edgesource is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. To request reasonable accommodation, please contact our Recruiting Department by email at recruiting@edgesource.com or by phone at (703) 837-0550.

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