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Mlops Machine Learning Engineer Jobs in Washington

CACI

Machine Learning Engineer

Chantilly, VA · 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 ...

Tetra Tech

Machine Learning Engineer - Remote

Vienna, VA · On-site

$120 - $180/hr

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 ...

Halvik

Machine Learning Engineer - Remote

Vienna, VA · 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 ...

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Mlops Machine Learning Engineer information

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 Washington?

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

What job categories do people searching Mlops Machine Learning Engineer jobs in Washington look for?

The top searched job categories for Mlops Machine Learning Engineer jobs in Washington are:

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Cities in Washington with the most Mlops Machine Learning Engineer job openings:

Mlops Machine Learning Engineer jobs near you

Artificial Intelligence & Machine Learning Engineer

Booz Allen Hamilton

Arlington, VA • On-site

$77.60 - $176/hr

Other

Medical, Life, Retirement, PTO

Re-posted 14 days ago

Booz Allen Hamilton rating

8.9

Company rating: 8.9 out of 10

Based on 49 frontline employees who took The Breakroom Quiz

11th of 72 rated business consultants

Job description

Artificial Intelligence & Machine Learning Engineer

The Opportunity:

As an experienced AI/ML engineer, you know that modern machine learning requires more than accurate models, it demands strong engineering practices, thoughtful system design, and the ability to build solutions that perform reliably in production. Your ability to conduct statistical analyses, implement AI/ML techniques, and build robust AI/ML pipelines makes you integral to delivering customer‑focused solutions. We need your technical expertise and problem‑solving mindset to support AI/ML missions across the federal government. As an AI/ML engineer on our team, you’ll design, train, test, deploy, and maintain end‑to‑end AI/ML systems, ensuring models perform reliably not just in development, but in production.

In this role, you’ll own and define the direction of mission‑critical solutions by selecting best‑fit algorithms, architecting AI/ML pipelines, and applying modern MLOps practices. You’ll be part of a talented team of machine learning engineers across the company and collaborate with data engineers, data scientists, software engineers, and product owners to deliver world‑class solutions. Your skills and technical leadership will guide clients as they navigate the landscape of AI/ML tools, frameworks, and operational strategies.

Work with us to solve real‑world challenges and define AI/ML strategy for the Defense sector and beyond.

Join us. The world can’t wait.

You Have
  • 4+ years of experience as an Artificial Intelligence/Machine Learning Engineer or Advanced Data Scientist
  • Experience deploying and integrating production‑grade AI/ML models using tools such as Docker or Kubernetes
  • Experience with Large Language Models (LLMs), Deep Learning (DL) or Reinforcement Learning (RL) algorithms, along with frameworks such as TensorFlow, PyTorch, vLLM, and Ollama
  • Knowledge of MLOps principles and the design and implementation of machine learning algorithms integrated in operational systems and deployed to production environments
  • Ability to train, optimize, and integrate AI/ML algorithms across high throughput text, image, or video data feeds
  • Secret clearance
  • Bachelor's degree
Nice If You Have
  • Experience working in cloud environments, such as AWS or Azure
  • Experience developing production‑quality ML‑enabled software components, such as RESTful APIs, microservices, or real‑time inference pipelines
  • Experience with emerging agentic AI frameworks and understanding of how to integrate agent‑based systems into production environments
  • TS/SCI clearance
  • 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 and Benefits

Salary range: $77,600.00 to $176,000.00 (annualized USD).

Benefits include health, life, disability, financial, and retirement benefits, paid leave, professional development, tuition assistance, work‑life programs, and dependent care. 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.

EEO Statement

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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What Booz Allen Hamilton employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Booz Allen Hamilton

Sourced by ZipRecruiter

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

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