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Mlops Machine Learning Engineer Jobs in Virginia

Cymertek Corporation

Machine Learning Engineer

Reston, VA · On-site

$110 - $170/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Steampunk

MLOps Engineer

Mclean, VA · On-site

$115K - $150K/yr

We are seeking a MLOps Engineer to design, build, and support the infrastructure, tooling, and automation that enable scalable and reliable machine learning systems across our client engagements.

Cymertek

Machine Learning Engineer

Reston, VA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA

$77K - $176K/yr

  • Medical

  • Life

  • Retirement

  • PTO

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 ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

  • Medical

  • Life

  • Retirement

  • PTO

R0242757 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 ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

  • Medical

  • Life

  • Retirement

  • PTO

R0245170 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 ...

Booz Allen Hamilton

Machine Learning Engineer

Alexandria, VA · On-site

$77K - $176K/yr

  • Medical

  • Life

  • Retirement

  • PTO

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 ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

  • Medical

  • Life

  • Retirement

  • PTO

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 ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

  • Medical

  • Life

  • Retirement

  • PTO

R0242766 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 ...

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Showing results 21-40

All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Virginia

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 Virginia?

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

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

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

What cities in Virginia are hiring for Mlops Machine Learning Engineer jobs?

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

Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops Machine Learning Engineer job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer - Computer Vision

CaseGuard

Arlington, VA • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 9 days ago

Job description

We are seeking a highly skilled and motivated Machine Learning Engineer specializing in Computer Vision to join our team. The ideal candidate will have a strong background in developing and deploying machine learning models focused on image and video processing. You will work closely with cross-functional teams to design, implement, and optimize vision-based AI solutions to address real-world challenges.
Key Responsibilities:
  • Design, develop, and deploy computer vision models for tasks such as object detection, object tracking, video segmentation, and facial recognition.
  • Optimize and fine-tune deep learning algorithms for real-time performance.
  • Work closely with the software engineers and product teams to identify opportunities for leveraging data.
  • Collect, clean, and preprocess large datasets to prepare for model training and evaluation.
  • Evaluate and optimize machine learning models for accuracy, performance, and scalability.
  • Deploy models into production environments and monitor their performance to ensure reliability.
  • Stay up-to-date with the latest advancements in computer vision and artificial intelligence.
  • Collaborate with cross-functional teams to integrate machine learning solutions into business processes.
  • Document processes, models, and implementations to ensure reproducibility and scalability.

Required Qualifications:
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Experience in deep learning models, their training, and hyperparameter tuning using libraries such as TensorFlow, PyTorch, and Transformers or other Huggingface tools.
  • Experience with data manipulation tools such as Pandas, NumPy, and SQL.
  • Strong programming skills in Python and C++.
  • Experience in MLOps principles and model deployment and instrumentation on cloud platforms such as AWS, Azure, or Google Cloud for model deployment and knowledge with efficient serving tools such as ONNX, triton, and vllm.
  • Proficiency in working with image and video data, including preprocessing and augmentation techniques.
  • Strong understanding of machine learning algorithms, including supervised and unsupervised learning and deep learning.
  • Strong communication skills and the ability to work collaboratively in a team environment.

Great to have:
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
  • Experience with version control systems such as Git.
  • Understanding software engineering best practices, including code review, testing, and documentation.
  • Experience with Large Language Models (LLMs) is a great plus.
  • Experience with data annotation tools and processes.

Benefits:
  • Competitive Salary
  • Stock Option
  • Medical, Dental, and Vision Insurance
  • 401K
  • Paid Vacation
  • Ten paid holidays per year
  • Friendly and Learning environment

About CaseGuard
CaseGuard is a software company that helps law enforcement agencies, federal agencies, hospitals, schools, airports, and others manage all their media redaction needs in one easy-to-use redaction software. CaseGuard Studio is one of a kind. Our team is driven by a passion for great software design, creating great products, and creative processes; CaseGuard implements innovative ideas across multiple services and agencies. We invest in people. We nurture skills consistent with our values and our future strategy. Our passionate pursuit of excellence, the application of our creativity to solve our clients' challenges, our technical expertise, and our collaborative spirit are measures of our success.

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