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Machine Learning Engineer From Home Jobs in Quantico, VA

The Jernigan Agency

WORK FROM HOME

Fredericksburg, VA · On-site +1

$300 - $500/wk

We are looking for individuals interested in working from home, remotely, as life insurance sales ... Lead system for getting in front of clients If you are interested in learning more about working ...

Phase2 Technology

Data Scientist, Mid

Springfield, VA · On-site

$77.60 - $176/hr

Professional certifications such as Google Professional Machine Learning Engineer, Azure Data ... This posting will close within 90 days from the Posting Date. Identity Statement As part of the ...

Leidos

AIOps Engineer SME

Fort Belvoir, VA · On-site

You will utilize Splunk and the Machine Learning Toolkit (MLTK) to provide descriptive and ... Normalize and correlate network performance and fault data from SolarWinds with server and ...

SCCI

Junior Engineer/Analyst

King George, VA · On-site

... and machine learning operations. The main duty for this position is to design, optimize, and ... A Bachelor of Science (BS) degree from an accredited college or university in Computer Science ...

ValidaTek, Inc.

AI Ops Engineer

Fort Belvoir, VA · On-site

$90K - $110K/hr

From customers to partners to top-talent employees, ValidaTek puts people first, empowering them to ... The role leverages Splunk and the Machine Learning Toolkit (MLTK) to deliver descriptive and ...

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Showing results 41-60

All JobsMachine Learning Engineer JobsMachine Learning Engineer From Home JobsMachine Learning Engineer From Home Jobs in Quantico, VA

Machine Learning Engineer From Home information

See Quantico, VA salary details

$33.4K

$136.4K

$205K

How much do machine learning engineer from home jobs pay per year?

As of Aug 18, 2026, the average yearly pay for machine learning engineer from home in Quantico, VA is $136,391.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $164,200.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Engineer From Home vs Data Scientist?

AspectMachine Learning Engineer From HomeData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRemote, flexible hours, often project-basedRemote or on-site, collaborative teams, research-focused
Employer & Industry UsageTech companies, startups, AI firmsTech, finance, healthcare, research institutions
Common Search & ComparisonOften compared for technical skills and remote work optionsCompared for data analysis and modeling expertise

While both roles require strong technical credentials and often involve remote work, Machine Learning Engineers From Home focus on developing and deploying ML models, whereas Data Scientists analyze data to generate insights. The choice depends on whether you prefer building algorithms or interpreting data trends.

Can a machine learning engineer work from home?

Yes, many machine learning engineers can work from home, especially in roles that involve data analysis, model development, and coding using tools like Python and TensorFlow. Remote work is common in this field, provided the engineer has a reliable internet connection, access to necessary hardware, and effective communication skills.

What are the most commonly searched types of Machine Learning Engineer jobs in Quantico, VA?

The most popular types of Machine Learning Engineer jobs in Quantico, VA are:

What are popular job titles related to Machine Learning Engineer From Home jobs in Quantico, VA?

For Machine Learning Engineer From Home jobs in Quantico, VA, the most frequently searched job titles are:

What cities near Quantico, VA are hiring for Machine Learning Engineer From Home jobs?

Cities near Quantico, VA with the most Machine Learning Engineer From Home job openings:

Machine Learning Engineer From Home jobs near you
Infographic showing various Machine Learning Engineer From Home job openings in Quantico, VA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, and 3% Contract. Highlights an 79% Physical, 1% Hybrid, and 20% Remote job distribution, with an average salary of $136,391 per year, or $65.6 per hour.

AI/ML Engineer with Security Clearance

Information Technology Engineering Corporation

Alexandria, VA • On-site

Other

Posted 28 days ago

Job description


AI/ML Engineer 
Location: Alexandria, VA/Springfield, VA/Arlington, VA/Herndon, VA/Chantilly, VA 
Required Clearance: Secret/Top Secret/Top Secret/SCI  Since 1999, ITEC has delivered mission-critical support to the DoD and Intelligence Community. Now part of ManpowerGroup Public Sector (MGPS), we continue that work with expanded capabilities. Employees hired through this process will join MGPS and receive a comprehensive benefits package and competitive pay.   U.S. Citizenship Mandatory: Due to our US federal government contract, candidates for this position are required to be a US Citizen and will be subject to a background investigation.   Job Responsibilities: * Design, build, and maintain AI/ML lifecycle core services and products. This person will create utilities and ensure seamless function of orchestration capabilities to support the AI/ML environment. * Develop and implement infrastructure for training, validating, and deploying machine learning models, create reusable components and libraries to accelerate AI/ML development, and build model serving platforms for efficient inference. * Implement automated machine learning pipelines, design systems for model monitoring and performance tracking, and develop tools for model explainability and interpretability. * Optimize AI/ML algorithms for performance and scalability, implement MLOps practices for continuous integration and deployment of models, and collaborate with data engineers to ensure data pipelines support AI/ML requirements. * Stay current with advances in AI/ML technologies, document AI/ML systems and processes, and provide technical guidance to data scientists implementing models. * Troubleshoot complex issues in AI/ML systems, implement version control for models and datasets, and develop testing frameworks for AI/ML components.

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