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Machine Learning Part Time Jobs in Virginia (NOW HIRING)

Booz Allen Hamilton, Inc.

AI/ML Engineer, Mid

Chantilly, VA · On-site +1

$77K - $176K/yr

As a machine learning engineer on our national security team, you'll train, test, deploy, monitor ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist, Mid

Reston, VA · On-site +1

$77K - $176K/yr

Experience with machine learning, AI, or NLP * Experience applying and querying SIGINT, GEOINT ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist

Arlington, VA · On-site +1

$69K - $158K/yr

... machine learning, and artificial intelligence. If you care about moving a mission forward as much ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist

Mclean, VA · On-site +1

$99K - $225K/yr

Experience developing production-quality machine learning models or pipelines * Experience with ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

AI & ML Engineer

Chantilly, VA · On-site +1

$99K - $225K/yr

As a machine learning engineer on our national security team, you'll train, test, deploy, and ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Computer Scientist

Mclean, VA · On-site

$99K - $225K/yr

... by IoT, machine learning, and artificial intelligence (AI). If you care about moving a mission ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist, Mid

Reston, VA · On-site +1

$77K - $176K/yr

Experience with machine learning, AI, or NLP * Experience applying and querying SIGINT, GEOINT ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Engineer

Arlington, VA · On-site +1

$62K - $141K/yr

Ever-expanding technology like IoT, machine learning, and artificial intelligence means that there ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

BOOZ, ALLEN & HAMILTON, INC.

Data Engineer

Arlington, VA · On-site

$141K/yr

Ever-expanding technology like IoT, machine learning, and artifi cia l intelligence means that ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist, Mid

Mclean, VA · On-site

$99K - $225K/yr

Knowledge of statistical analysis, predictive modeling, and machine learning methods * Ability to ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

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Showing results 41-60

All JobsMachine Learning JobsMachine Learning Part Time JobsMachine Learning Part Time Jobs in Virginia

Machine Learning Part Time information

See Virginia salary details

$25.3K

$42.2K

$87.2K

How much do machine learning part time jobs pay per year?

As of Aug 18, 2026, the average yearly pay for machine learning part time in Virginia is $42,218.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

What is a machine learning part time job?

A Machine Learning Part Time job is a role where individuals work on ML-related tasks with a flexible or reduced schedule. These roles can involve data preprocessing, model development, evaluation, or deployment, depending on the organization's needs. Part-time positions are often suitable for students, freelancers, or professionals looking to gain experience while managing other commitments. They may be remote or on-site and can vary in duration and workload.

What are the typical responsibilities and expectations for a part-time machine learning role?

In a part-time machine learning position, you are generally expected to assist with data preprocessing, model development, and analysis of project results under the guidance of a senior data scientist or engineer. Your tasks might include cleaning datasets, coding algorithms, running experiments, and preparing reports or presentations for team meetings. The work is often project-based and requires regular communication with team members to ensure alignment on objectives and deliverables. This structure allows you to gain hands-on experience with real-world datasets and industry tools while maintaining a flexible schedule, making it ideal for students or professionals transitioning into the field.

What are the key skills and qualifications needed to thrive in the machine learning part time position, and why are they important?

To thrive as a Machine Learning Part Time professional, you need a strong foundation in statistics, programming (often Python or R), and knowledge of core machine learning algorithms, typically demonstrated through a degree in computer science, engineering, or a related field. Familiarity with frameworks such as TensorFlow, Scikit-learn, or PyTorch and experience with data preprocessing tools or cloud platforms are commonly expected, and certifications like TensorFlow Developer can be beneficial. Effective communication, time management, and the ability to work independently are key soft skills for success in this role. These competencies enable you to efficiently contribute to projects, solve complex problems, and collaborate remotely or in hybrid team environments.

What are the most commonly searched types of Machine Learning jobs in Virginia?

The most popular types of Machine Learning jobs in Virginia are:

What are popular job titles related to Machine Learning Part Time jobs in Virginia?

For Machine Learning Part Time jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Machine Learning Part Time jobs in Virginia look for?

The top searched job categories for Machine Learning Part Time jobs in Virginia are:

What cities in Virginia are hiring for Machine Learning Part Time jobs?

Cities in Virginia with the most Machine Learning Part Time job openings:

Machine Learning Part Time jobs near you
Infographic showing various Machine Learning Part Time 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, with an average salary of $42,218 per year, or $20.3 per hour.

Technical Advisor - Cloud, Application, Data & AI

Oran Inc

Herndon, VA • Remote

Part-time

Posted 6 days ago

Job description

Position: Technical Advisor
Employment Type: Part-Time / Hourly
Work Location: Remote
Engagement: Hourly / Consulting
Customer Focus: U.S. Federal Government

Position Overview

We are seeking an experienced Technical Advisor to provide part-time, senior-level technical guidance and solutioning support for our internal teams and Federal Government customer engagements.

The Technical Advisor will serve as a trusted technical resource responsible for developing and reviewing technical solutions, architectures, approaches, and responses across Cloud, Application, Data, Artificial Intelligence, Cybersecurity, and other emerging technology areas.

This is an advisory and solutioning-focused role. The ideal candidate should be able to quickly understand customer requirements, translate business and mission needs into practical technical solutions, and help teams develop compelling and technically sound approaches for Federal customers.

Key Responsibilities
  • Serve as an internal technical advisor and subject matter expert for Federal customer opportunities and projects.
  • Develop high-level and detailed technical solutions and solution architectures based on customer requirements.
  • Provide technical expertise across:
    • Cloud: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP)
    • Application Architecture & Modernization
    • Data Engineering, Data Platforms & Analytics
    • Artificial Intelligence (AI), Generative AI (GenAI) & Machine Learning
    • Application Programming Interfaces (APIs) and Microservices
    • Cybersecurity and Zero Trust
    • DevSecOps, Infrastructure as Code (IaC) and Cloud Automation
    • Containers, Kubernetes and Cloud-Native Architecture
    • Data & AI platforms, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and AI-enabled solutions
    • Other emerging and high-growth technologies relevant to Federal IT modernization.
  • Analyze Requests for Information (RFIs), Requests for Proposals (RFPs), Statements of Work (SOWs), Performance Work Statements (PWSs), and Statements of Objectives (SOOs) and translate requirements into technical approaches.
  • Develop technical solution concepts, architecture diagrams, technology stacks, implementation approaches, and solution narratives.
  • Support proposal solutioning, technical writing, and technical reviews.
  • Collaborate with business development, capture, proposal, recruiting, and delivery teams to develop technically competitive solutions.
  • Evaluate emerging technologies and recommend where they can provide value to Federal customers.
  • Review proposed technical approaches for feasibility, scalability, security, cost, and alignment with Federal requirements.
  • Provide technical mentorship and guidance to internal teams.
  • Participate in customer discussions, technical briefings, solution presentations, and architecture reviews when required.
  • Help identify technology partners, platforms, tools, and technical capabilities needed to support customer requirements.
Required Qualifications
  • 10+ years of progressive experience in technology, IT architecture, engineering, consulting, or technical solutioning.
  • Demonstrated experience developing technical solutions and architectures for complex enterprise environments.
  • Strong knowledge of at least two major cloud platforms, preferably AWS, Azure, and/or GCP.
  • Broad understanding of modern Application, Data, Cloud, AI, and Cybersecurity technologies.
  • Experience translating complex technical requirements into clear, actionable solution approaches.
  • Strong technical writing and presentation skills.
  • Experience supporting Federal Government customers, contracts, proposals, or solutioning efforts.
  • Ability to work independently in a part-time advisory capacity and provide expertise when needed.
  • Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders.
Preferred Qualifications
  • Experience with Federal IT modernization and cloud transformation.
  • Experience with Enterprise Architecture, Cloud Architecture, Solution Architecture, or Technical Architecture.
  • Knowledge of Federal technology and security frameworks such as:
    • National Institute of Standards and Technology (NIST)
    • Federal Risk and Authorization Management Program (FedRAMP)
    • Federal Information Security Modernization Act (FISMA)
    • Zero Trust Architecture
    • NIST Cybersecurity Framework
  • Experience with Artificial Intelligence, Generative AI, Machine Learning, Large Language Models, Retrieval-Augmented Generation, AI Agents, or AI governance.
  • Experience with cloud-native technologies, Kubernetes, containers, Infrastructure as Code, and DevSecOps.
  • Experience supporting Requests for Proposals (RFPs), Requests for Information (RFIs), Sources Sought, and government technical responses.
  • Relevant certifications such as:
    • AWS Certified Solutions Architect
    • Microsoft Certified: Azure Solutions Architect Expert
    • Google Cloud Professional Cloud Architect
    • Certified Information Systems Security Professional (CISSP)
    • Certified Cloud Security Professional (CCSP)
    • TOGAF certification
    • Other relevant cloud, architecture, cybersecurity, data, or AI certifications.
Ideal Candidate

The ideal candidate is a technology generalist with deep expertise in architecture and solutioning rather than someone limited to a single technology stack.

You should be able to walk into a Federal customer requirement, understand the mission and technical challenges, and answer:

“What should we build, how should we build it, what technologies should we use, and why is this the right solution?”

The candidate should be comfortable moving between Cloud + Application + Data + AI + Security + Emerging Technologies and providing practical, commercially viable recommendations.

Engagement Details
  • Part-Time
  • Remote
  • Hourly Consulting Engagement
  • Flexible hours based on project and proposal requirements
  • Primarily internal advisory and Federal customer support
  • Opportunity to support multiple Federal technology initiatives and proposals