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Mlops Machine Learning Engineer Jobs in Ashburn, VA

Machine Learning Engineer

Chantilly, VA ยท On-site

$131K - $290K/yr

Machine Learning Engineer Job Category: Information Technology Time Type: Full time Minimum ... knowledge of MLOps practices for ML model deployment and monitoring Experience with container ...

Deployment & MLOps * Operationalize models with robust CI/CD workflows. * Deploy models usingMLflow ... Required Skills: * 5+ years of experience in ML Engineering or Applied Machine Learning. * Strong ...

Machine Learning Engineer - Remote

Vienna, VA ยท Remote

$140K - $150K/yr

Deployment & MLOps * Operationalize models with robust CI/CD workflows. * Deploy models usingMLflow ... Required Skills: * 5+ years of experience in ML Engineering or Applied Machine Learning. * Strong ...

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Machine Learning Engineer

Reston, VA ยท On-site

$110 - $170/hr

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Showing results 21-40

Mlops Machine Learning Engineer information

See Ashburn, VA salary details

$32.2K

$131.7K

$197.9K

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

As of Sep 3, 2026, the average yearly pay for mlops machine learning engineer in Ashburn, VA is $131,680.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,800.00 and $158,500.00 per year, depending on experience, location, and employer.

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.

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

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.

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 machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning 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 and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Ashburn, VA?

For Mlops Machine Learning Engineer jobs in Ashburn, VA, the most frequently searched job titles are:

Infographic showing various Mlops Machine Learning Engineer job openings in Ashburn, VA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 25% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $131,680 per year, or $63.3 per hour.

Machine Learning Engineer

CACI

Chantilly, VA โ€ข On-site

$131K - $290K/yr

Full-time

Medical, Retirement, PTO

Posted 5 days ago


Job description

Job Title: Machine Learning Engineer Job Category: Information Technology Time Type: Full time Minimum Clearance Required to Start: TS/SCI with Polygraph Employee Type: Regular Percentage of Travel Required: None Type of Travel: None * * * The Opportunity: CACI is seeking a Software Developer with AI experience to join our dynamic team. This role will focus on developing and implementing AI solutions to enhance our enterprise-level IT operations. The Developer will work closely with cross-functional teams to design, develop, and deploy AI-driven applications that improve efficiency, automate processes, and provide valuable insights.

Responsibilities: Develop and maintain machine learning pipelines and applications using Python and modern ML frameworks Implement and optimize algorithms for large language model (LLM) integration and deployment Build RESTful APIs and microservices to serve ML models in production environments Write clean, maintainable, and well-documented code following object-oriented programming principles Collaborate with cross-functional teams to understand requirements and translate them into technical solutions Work with databases (SQL,NoSQL and Vector) to manage training data, model artifacts, and application state Containerize ML applications using Docker for consistent deployment across environments Utilize Git for version control and participate in code reviews to maintain code quality Conduct testing and debugging of ML applications to ensure reliability and accuracy Support the deployment and monitoring of AI/ML models in cloud environments Stay current with emerging trends in machine learning, LLMs, and AI engineering best practices Qualifications: Required: Active TS/SCI clearance with Poly Bachelor's degree in computer science, Software Engineering, Data Science, or related technical field with 5 years of professional experience in software development or machine learning engineering Strong proficiency in Python programming with solid understanding of object-oriented programming (OOP) concepts, design patterns, data structures, and algorithms Experience with development tools and practices including Git version control, Docker containerization, and database management (SQL and/or NoSQL) Knowledge of LLM technologies including exposure to Large Language Models, orchestration frameworks (LangChain, LangGraph), Understanding of RAG architectures and vector databases (ChromaDB, Pinecone, Weaviate, or similar) for building intelligent retrieval systems Strong problem-solving abilities, attention to detail, excellent communication skills, and eagerness to learn in a collaborative team environment Desired: Master's degree in computer science or related field Experience with cloud platforms (AWS, Azure, or Google Cloud) and knowledge of MLOps practices for ML model deployment and monitoring Experience with container orchestration and DevOps including Kubernetes, Rancher, CI/CD pipelines, and infrastructure automation tools like Ansible Familiarity with enterprise platforms such as ServiceNow, SAP, Tableau, or Splunk Contributions to open-source ML projects and familiarity with Agile development methodologies - What You Can Expect: A culture of integrity. At CACI, we place character and innovation at the center of everything we do. As a valued team member, you'll be part of a high-performing group dedicated to our customer's missions and driven by a higher purpose - to ensure the safety of our nation.

An environment of trust. CACI values the unique contributions that every employee brings to our company and our customers - every day. You'll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality.

A focus on continuous growth. Together, we will advance our nation's most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground - in your career and in our legacy. Pay Range: There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications.

Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families.

At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits. The proposed salary range for this position is: $131,800 - $290,000 CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any other protected characteristic.