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Patterned Learning Ai Jobs in Virginia (NOW HIRING)

RIVA Solutions Inc.

Low Code AI Engineer

Reston, VA · Remote

... patterns, and support the knowledge/content lifecycle that powers AI experiences (e.g., ingestion, validation, refresh, governance, and monitoring). Traditional, heavy machine learning model ...

RIVA Solutions Inc.

Low Code AI Engineer

Reston, VA · Remote

... patterns, and support the knowledge/content lifecycle that powers AI experiences (e.g., ingestion, validation, refresh, governance, and monitoring). Traditional, heavy machine learning model ...

Whitespace

AI Software Developer

Alexandria, VA · On-site +1

At Whitespace, we use our Iris platform to uncover hidden relationships and patterns of life (POL ... Learning, or a related field is desired but not required. Will consider experience in lieu of a ...

Vantor

AI/ML Engineer (Senior)

Reston, VA · On-site

$108K - $149K/yr

... pattern recognition, target detection and tracking, machine learning and decision systems • May use system-of-systems and multi-agent approaches to architect and design AI software systems ...

Fannie Mae

Principal, AI Solutions

Reston, VA · On-site

Lead the AI solutions layer, translating platform capabilities into repeatable enterprise patterns ... Machine Learning Engineer - Principal 200,000.00 - 269,000.00 JR2676 Qualifications Artificial ...

Fannie Mae

Principal, AI Solutions

Reston, VA

Lead the AI solutions layer, translating platform capabilities into repeatable enterprise patterns ... Machine Learning Engineer - Principal 200,000.00 - 269,000.00 JR2676 Qualifications Artificial ...

Fanniemae

Principal, AI Solutions

Reston, VA

Lead the AI solutions layer, translating platform capabilities into repeatable enterprise patterns ... Machine Learning Engineer - Principal 200,000.00 - 269,000.00 JR2676 Qualifications Artificial ...

Vantor

AI/ML Engineer (SME)

Arlington, VA · On-site

... pattern recognition, target detection and tracking, machine learning and decision systems • May use system-of-systems and multi-agent approaches to architect and design AI software systems ...

Visa

Software Engineer

Ashburn, VA · On-site

$88K/yr

Design and develop backend services and APIs using Python (FastAPI) and distributed system patterns ... Coursework or projects related to machine learning, AI systems, or workflow automation U.S.

Vantor

AI/ML Engineer (Senior)

Reston, VA · On-site

$108K - $149K/yr

... pattern recognition, target detection and tracking, machine learning and decision systems • May use system-of-systems and multi-agent approaches to architect and design AI software systems ...

Vantor

AI/ML Engineer (Senior)

Arlington, VA · On-site

$120K - $165K/yr

... pattern recognition, target detection and tracking, machine learning and decision systems • May use system-of-systems and multi-agent approaches to architect and design AI software systems ...

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All JobsPatterned Learning Ai JobsPatterned Learning Ai Jobs in Virginia

Patterned Learning Ai information

What are some typical challenges faced by patterned learning AI professionals in implementing AI-driven solutions within organizations?

Patterned Learning AI professionals often encounter challenges such as integrating AI models with existing legacy systems, ensuring high-quality and representative training data, and aligning AI solutions with specific business objectives. Collaboration across multidisciplinary teams—including data scientists, software engineers, and business stakeholders—is essential for successful deployment. Additionally, professionals must stay updated on evolving AI technologies and best practices to maintain model accuracy and address ethical considerations.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (especially Python), and a degree in computer science or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, as well as familiarity with cloud computing platforms and data management tools, is essential. Excellent problem-solving skills, creativity, and clear communication are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies are vital for developing reliable AI systems that solve real-world problems and drive innovation.

What is the difference between Patterned Learning Ai vs Data Scientist?

AspectPatterned Learning AiData Scientist
Required CredentialsTypically requires machine learning, AI, or computer science degrees; certifications in AI toolsRequires degrees in statistics, computer science, or related fields; often certifications in data analysis
Work EnvironmentTech companies, AI startups, research labs focusing on AI developmentBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed by AI-focused organizations developing intelligent systemsEmployed across industries for data analysis, predictive modeling, and decision support

Patterned Learning Ai primarily focuses on developing AI models and algorithms, often requiring specialized technical skills. Data Scientists analyze data to extract insights and inform business decisions. While both roles involve data and machine learning, Patterned Learning Ai is more centered on creating AI systems, whereas Data Scientists interpret data for strategic purposes.

What is patterned learning AI?

Patterned Learning AI refers to artificial intelligence systems designed to recognize, learn from, and replicate patterns in data. These systems use algorithms to identify trends, correlations, and structures within large datasets, enabling them to make predictions or automate decision-making processes. Patterned Learning AI is commonly used in fields like image recognition, natural language processing, and predictive analytics. Its applications help businesses and researchers uncover hidden insights, streamline operations, and improve accuracy in various tasks.
What are popular job titles related to Patterned Learning Ai jobs in Virginia? For Patterned Learning Ai jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Patterned Learning Ai jobs in Virginia look for? The top searched job categories for Patterned Learning Ai jobs in Virginia are:
What cities in Virginia are hiring for Patterned Learning Ai jobs? Cities in Virginia with the most Patterned Learning Ai job openings:
Patterned Learning Ai jobs near you
Infographic showing various Patterned Learning Ai job openings in Virginia as of July 2026, with employment types broken down into 1% As Needed, 70% Full Time, 25% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Low Code AI Engineer

RIVA Solutions Inc.

Reston, VA • Remote

Full-time

This job post has expired today. Applications are no longer accepted.

Job description







Title: Low Code AI Engineer  

Location: Remote within the United States  

Terms: Full-time  

Clearance: U.S. Citizenship required and ability to obtain and maintain a Federal Public  

Trust investigation  

Travel: 0–10%  

RESULTS. INNOVATION. VALUES. ACCOUNTABILITY.  

That’s RIVA. Our employee-first approach has manifested a culture that attracts the best  

and brightest. By investing in people first and providing a flexible work environment, our  

employees have higher morale, higher productivity rates, and lower turnover. At RIVA,  

people are our #1 priority.  

Program Overview  

RIVA Solutions supports the U.S. Department of Commerce (DOC), International Trade  

Administration (ITA), in establishing and operating an AI Center of Excellence (AI-CoE)  

under the Office of the Chief Information Officer (OCIO). This program advances IT  

modernization by designing, developing, deploying, and maintaining artificial intelligence  

and machine learning solutions that strengthen mission outcomes across the Commerce  

enterprise.  

The AI-CoE provides AI application development, model lifecycle management, data  

engineering, security support, quality assurance, and Agile delivery services that enable  

DOC to mature toward higher levels of operational and technological excellence. RIVA’s  

work ensures that AI tools and systems are reliable, scalable, secure, and aligned with  

federal cloud and data strategies.  

Position Overview  

RIVA Solutions is seeking a Low Code AI Engineer to support the delivery and  

operationalization of AI-enabled solutions using low-code platforms—primarily Microsoft  

Power Platform and Copilot Studio—within the AI Center of Excellence. This role focuses  

on enabling, deploying, integrating, and monitoring AI experiences in Microsoft’s  

specialized government cloud environment (Government Cloud Computing/Government  

Community Cloud), designed to meet the compliance and security needs of Federal, State,  






Local, and Tribal governments. Emphasis is placed on configuration-first development,  

CI/CD, data/content ingestion pipelines, and ongoing operations to ensure reliable  

production performance.  

This position partners closely with technical teams and federal stakeholders to implement  

scalable low-code solutions, establish repeatable delivery patterns, and support the  

knowledge/content lifecycle that powers AI experiences (e.g., ingestion, validation, refresh,  

governance, and monitoring). Traditional, heavy machine learning model development is  

not a primary expectation for this role, though limited support may be required as future  

mission use cases evolve.  

U.S. Citizenship is required, along with the ability to obtain and maintain a federal Public  

Trust investigation. This position is fully remote within the United States.  

Core Responsibilities  

•

•

Enable and deliver low-code AI solutions using Microsoft Power Platform and  

Copilot Studio to support enterprise mission needs.  

Configure, integrate, and operationalize AI experiences, including connectors,  

workflows, approvals, and automation patterns that support secure enterprise  

adoption.  

•

Support cloud delivery within Microsoft’s specialized government cloud  

environment (Government Cloud Computing/Government Community Cloud),  

ensuring solutions align with federal security, compliance, and governance  

requirements.  

•

•

Implement and maintain CI/CD processes for Power Platform/Copilot solutions  

(solution packaging, environment promotions, release management, and  

deployment automation).  

Build and support data/content ingestion pipelines that prepare and maintain  

knowledge sources for AI experiences (knowledge lifecycle management,  

validation, refresh schedules, and quality checks).  

•

•

Deploy, monitor, and optimize low-code AI solutions in production, including  

telemetry, alerting, performance monitoring, and incident response support.  

Partner with Data Engineers and platform teams to ensure content and data are  

structured, accessible, and maintained for AI-enabled experiences (without  

requiring heavy feature engineering or predictive modeling).  

Use Python or lightweight scripting only as needed for function calls, integration  

edge cases, automation gaps, or specialized operational support.  

•






•

•

•

Document platform configurations, release procedures, operational runbooks,  

integration patterns, and technical implementation details.  

Collaborate with AI Developers, Data Engineers, Scrum Masters, and federal  

stakeholders in Agile/Scrum environments.  

Stay informed on emerging low-code AI capabilities (Power Platform, Copilot Studio,  

governance, and federal cloud guidance) to improve solution quality and  

maintainability.  

Minimum Qualifications  

•

•

Bachelor’s degree or equivalent professional experience.  

Minimum 2 years of experience delivering low-code solutions, platform  

enablement, automation, or related engineering work (Power Platform/Copilot  

Studio strongly preferred).  

•

•

Experience configuring, deploying, and supporting solutions across multiple  

environments (dev/test/prod), including release and change management practices.  

Experience with CI/CD concepts and implementation for low-code or platform-  

based solutions (packaging, deployments, environment strategy, and operational  

monitoring).  

•

Experience supporting data/content ingestion, integration, or lifecycle processes  

that enable AI experiences (knowledge management, data preparation workflows, or  

content operations).  

•

•

Apply