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Mlops Machine Learning Engineer Jobs in Virginia

Machine Learning Engineer LOCATIONTysons, VA 22182 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Machine Learning Engineer LOCATIONChantilly, VA 20151 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

R0241353 Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to ...

Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct ...

Machine Learning Engineer LOCATIONReston, VA 20190 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

That's why we need you, an experienced machine learning engineer, to help us design and architect an MLOps platform in the Cloud that shortens the time it takes to get new capabilities from ...

Mid MLOps Engineer

Chantilly, VA · On-site

$77K - $176K/yr

That's why we need you, an experienced machine learning engineer, to help us design and architect an MLOps platform in the Cloud that shortens the time it takes to get new capabilities from ...

That's why we need you, an experienced machine learning engineer, to help us design and architect an MLOps platform in the Cloud that shortens the time it takes to get new capabilities from ...

Machine Learning Engineer Our clients, a rapidly growing AI-focused software development company supporting federal agencies, is seeking a Machine Learning Engineer. Delivers mission-critical ...

Senior Machine Learning Engineer

Mclean, VA

$107K - $147K/yr

Senior Machine Learning Engineer McLean, Virginia Senior Machine Learning Engineer Location: McLean ... MLOps & deployment: Experiment tracking, Docker, ONNX/TensorRT, deploying inference services to the ...

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Mlops Machine Learning Engineer information

Is MLOps harder than DevOps?

MLOps, as a specialized subset of DevOps focused on deploying and maintaining machine learning models, often involves additional challenges such as data management, model versioning, and monitoring. While both require skills in automation, scripting, and cloud environments, MLOps typically demands expertise in machine learning workflows and tools like TensorFlow or PyTorch, making it more complex in certain aspects compared to traditional DevOps.

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.

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 engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning models in various industries. Their skills in deploying, managing, and scaling machine learning systems, along with knowledge of tools like Docker, Kubernetes, and cloud platforms, make them valuable in the job market.

What engineers make $500,000?

Senior machine learning engineers, including those specializing in MLOps, often reach or exceed $500,000 annually with experience, advanced skills, and in high-demand industries like tech or finance. Compensation can include base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

How much do MLOps engineers make?

MLOps engineers typically earn between $100,000 and $150,000 annually, with salaries increasing based on experience, location, and expertise in tools like Kubernetes, Docker, and cloud platforms. Senior roles or those with specialized skills can exceed $180,000 per year.

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

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.
What cities in Virginia are hiring for Mlops Machine Learning Engineer jobs? Cities in Virginia with the most Mlops Machine Learning Engineer job openings:
Infographic showing various Mlops Machine Learning Engineer job openings in Virginia as of June 2026, with employment types broken down into 76% Full Time, 19% Part Time, and 5% Temporary. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Booz Allen Hamilton, Inc.

Mclean, VA • On-site

$77K - $176K/yr

Full-time, Part-time

Medical, Life, Retirement, PTO

Posted 28 days ago


Booz Allen Hamilton rating

8.8

Company rating: 8.8 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

9th of 57 rated business consultants


Job description

Job Description
Remote Work:
No
Job Number:
R0241353
Location:
McLean,VA,US
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Additional Locations:
  • Washington, District of Columbia, USA

Machine Learning Engineer
The Opportunity:
As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using ML techniques makes you an integral part of delivering a customer-focused solution. We need your technical knowledge and desire to problem-solve to support innovation across the DoD market. As a machine learning engineer on our defense technology team, you'll train, test, deploy, and maintain models that learn from data.
In this role, you'll own and define the direction of mission-critical solutions by implementing AI that enables faster mission success. You'll be part of a large community of machine learning engineers across the company and collaborate with data engineers, data scientists, solutions architects, and product owners to deliver world-class solutions to implement a wide variety of AI use cases. Your skills and extensive technical expertise will guide clients as they navigate the landscape of ML algorithms, tools, and frameworks.
Work with us to solve real-world challenges and define AI strategy for national security.
Join us. The world can't wait.
You Have:
  • 2+ years of experience with artificial intelligence, data science, or machine learning engineering, including developing and deploying models
  • Experience with Python coding and libraries, including scikit-learn, TensorFlow, or PyTorch
  • Experience with developing code using a common programming language, including Python, C++, Rust, or Java
  • Experience with deep learning, computer vision, or generative AI
  • Experience with data handling and model development
  • Ability to solve client issues and problems
  • Secret clearance
  • Bachelor's degree

Nice If You Have:
  • Experience with generative and agentic AI technologies, such as LLMs, MCP, LangChain, or LangGraph
  • Experience with supervised and unsupervised learning
  • Ability to develop and maintain scalable data stores that supply big data in forms needed for business analysis
  • Ability to create software for retrieving, parsing, and processing structured and unstructured data
  • Master's degree

Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; Secret clearance is required.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date.
Identity Statement
As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Candidate AI Usage Policy
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.
Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.
  • Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
  • Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.
  • Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
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About Booz Allen Hamilton

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Booz Allen Hamilton is a leading provider of management and technology consulting services to the US government in defense, intelligence, and civil markets. Headquartered in McLean, Virginia, the firm also serves major corporations, institutions, and not-for-profit organizations. Founded in 1914 by Edwin G. Booz, the company has a long-standing tradition of helping clients achieve success by delivering a wide range of consulting services that include strategic planning, human capital and learning, communication, systems development, and others. The company's mission is to empower people to change the world, and it has a reputation for maintaining the highest standards of integrity and-excellence.

Industry

It services

Company size

10,000+ Employees

Headquarters location

McLean, VA, US

Year founded

1914