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Mlops Machine Learning Engineer Jobs in Virginia

ML Engineer

Mclean, VA · On-site

$70 - $75/hr

Strong understanding of MLOps principles and the machine learning lifecycle * Experience with distributed data processing frameworks such as Apache Spark * Strong software engineering fundamentals ...

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Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Senior Machine Learning Engineer Location: McLean, VA (hybrid); occasional travel to Durham, NC and ... MLOps & deployment: Experiment tracking, Docker, ONNX/TensorRT, deploying inference services to the ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

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Showing results 1-20

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.

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.

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:
Agentic AI Machine Learning Engineer

Agentic AI Machine Learning Engineer

Booz Allen Hamilton

Mclean, VA

$99K - $225K/yr

Full-time

Medical, Life, Retirement, PTO

Re-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 58 rated business consultants


Job description

Agentic AI Machine Learning Engineer

The Opportunity:

As an experienced machine learning engineer, you understand goodsoftware is more than just a good user experience. To compete in today's technical landscape, mission-oriented machine learning solutions must be architected, designed, and built to handle fast-moving data, to seamlessly scale with infrastructure based on system usage, and to expand based on evolving mission requirements. We're looking for an engineer like you to create artificial intelligence (AI) and machine learning(ML)enabled solutions that help solve our toughest challenges facing the Defense and Intelligence sectors.

On our team, you'll design, create, and implement completeAI systems that will transform client operations, increase data accessibility, and optimize AI and ML systems. You'll ensure that your team's solutions consider the broader ecosystem and operating environment as well as future functionality and enhancements. Additionally, you'll deepen your skill set in areas likesoftware engineering, machine learning operations(MLOps), andsoftware deployment and integration into a variety of different mission environments.

Ready to transform the Defense and Intelligence sectors withsoftware systems to aid data accessibility and AI and ML operationalization?

Join us. The world can't wait.

You Have:

  • 3+ years of experience as a ML engineer and building production-grade ML solutions, including work involving LLMs, agents, or complex automation frameworks

  • 3+ years of experience working within data science or data research in a professional or academic environment, and training or deploying models across multiple modalities of data

  • 3+ years of experience working in cloud environments, including AWS and Azure

  • 2+ years of experience deploying and integrating production-grade ML models using tools, such as Docker and Kubernetes

  • Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL), and with tools and AI agent frameworks such as LangChain, LangGraph, PydanticAI, or llamaindex

  • Experience in connecting Agents to APIs, Cloud platforms, or databases

  • Experience evaluating LLM performance and building observation layers for stakeholders, including Grafana, Langfuse, LangSmith, or Phoenix

  • Experience evaluating architectural tradeoffs and designing robust service-based software applications for scalable use

  • Ability to obtain a Secret clearance

  • Bachelor's degree

Nice If You Have:

  • Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and vLLM

  • Experience with client engagements, client-facing project work, and business development

  • Experience with project work in deep learning, computer vision, NLP, or signal processing

  • Experience deploying and managing data brokering solutions, including Kafka, Red Panda, Confluent, and other related services

  • Ability to adapt in a rapidly changing environment

  • Possession of excellent verbal and written communication skills

  • Possession of excellent interpersonal, analytical, problem-solving, and organizational skills

  • Secret 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.

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 $99,000.00 to $225,000.00 (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

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