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Machine Learning Intern Jobs in Fairfax, VA (NOW HIRING)

Andersen

Intern - Commercial - 2027

Mclean, VA · On-site

$38.22/hr

As an Intern, you will be given a mentor to guide you throughout the experience and have the opportunity to build your professional network through various events and activities. Intern ...

Analytica

2027 Summer Intern Associate

Bethesda, MD

$16 - $21.50/hr

Data Science Intern * Assist with data analysis, modeling, and exploratory data analysis ... Support development of machine learning or statistical models * Prepare datasets for analysis and ...

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All JobsMachine Learning Intern JobsMachine Learning Intern Jobs in Fairfax, VA

Machine Learning Intern information

See Fairfax, VA salary details

$26.1K

$43.5K

$90K

How much do machine learning intern jobs pay per year?

As of Sep 2, 2026, the average yearly pay for machine learning intern in Fairfax, VA is $43,527.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,200.00 and $47,000.00 per year, depending on experience, location, and employer.

What does a machine learning intern do?

A Machine Learning Intern assists with developing, testing, and deploying machine learning models under the supervision of experienced data scientists or engineers. Their responsibilities may include data preprocessing, feature engineering, coding algorithms, analyzing results, and assisting with research tasks. Interns often work with programming languages like Python and libraries such as TensorFlow or PyTorch. The internship provides hands-on experience in real-world machine learning projects and helps interns build essential skills for a future career in the field.

What does a machine learning intern do?

A machine learning intern works in the field of data science. During an internship, you work alongside machine learning engineers who are developing artificial intelligence programs. They do this by writing computer code that allows a software system to run autonomously. Your exact responsibilities depend on the type and level of engineering that the company does. While you likely do not have coding duties, you may help the programmers test or debug their code. You may also work with algorithms and the mathematical aspects of artificial intelligence. A machine learning intern works under the supervision of a lead engineer.

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

To thrive as a Machine Learning Intern, you need a solid understanding of statistics, programming (especially Python), and foundational machine learning concepts, typically supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and data analysis libraries, as well as experience with version control systems like Git, is highly valuable. Strong problem-solving skills, curiosity, and effective communication set outstanding candidates apart in this role. These abilities are essential for analyzing data, building models, and collaborating with teams to develop innovative AI solutions.

What types of projects do machine learning interns typically work on, and how are they supported by the team?

Machine Learning Interns often contribute to real-world projects such as data preprocessing, developing and testing models, or assisting with research for new algorithms. Interns are usually paired with a mentor or work within a small team, receiving guidance during code reviews and regular check-ins. This collaborative environment helps interns gain practical experience, quickly overcome challenges, and integrate feedback, ensuring a steep learning curve and valuable industry exposure.

What is the difference between Machine Learning Intern vs Data Science Intern?

AspectMachine Learning InternData Science Intern
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed in companies developing AI products, research institutions, tech startupsCommon in organizations requiring data analysis, reporting, and decision-making support

While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.

More about Machine Learning Intern jobs

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

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

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For Machine Learning Intern jobs in Fairfax, VA, the most frequently searched job titles are:

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The top searched job categories for Machine Learning Intern jobs in Fairfax, VA are:

What cities near Fairfax, VA are hiring for Machine Learning Intern jobs?

Cities near Fairfax, VA with the most Machine Learning Intern job openings:

Machine Learning Intern jobs near you
Infographic showing various Machine Learning Intern job openings in Fairfax, VA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $43,527 per year, or $20.9 per hour.

Machine Learning / Federated-Learning Engineer

Steampunk

Mclean, VA • On-site

Other

Posted 8 days ago

Job description

Overview
We are seeking a Machine Learning (ML) / Federated-Learning Engineer responsible for developing, implementing, and supporting machine learning solutions within controlled and distributed environments. This role will support the Bounded Use Case B demonstration through controlled model adaptation, fine-tuning, and federated learning workflows.
The ML / Federated-Learning Engineer will work across the machine learning lifecycle to develop and integrate model training and adaptation workflows, support distributed and federated learning capabilities, evaluate model performance, and ensure solutions operate within defined technical and security constraints. This role requires strong hands-on experience with machine learning engineering, model development, and distributed computing environments.
Contributions
  • Design, develop, and implement machine learning solutions supporting the Bounded Use Case B demonstration
  • Develop and execute controlled model adaptation and fine-tuning workflows based on defined use cases and requirements
  • Design, implement, and support federated learning workflows that enable distributed model training and adaptation
  • Develop and maintain machine learning pipelines supporting data preparation, model training, fine-tuning, evaluation, and deployment
  • Analyze and preprocess data, including feature engineering and transformation, to support machine learning workflows
  • Configure and optimize machine learning models and training processes to meet defined performance and operational requirements
  • Evaluate model performance, behavior, and effectiveness using established metrics and validation techniques
  • Develop processes and controls to ensure model adaptation and training occur within defined technical, security, and operational boundaries
  • Integrate machine learning capabilities with existing applications, platforms, data sources, and infrastructure
  • Troubleshoot model training, integration, performance, and distributed learning issues
  • Develop reusable code, tools, and automation to support machine learning and federated learning workflows
  • Collaborate with data scientists, software engineers, cloud engineers, cybersecurity teams, and other technical stakeholders to develop and integrate machine learning capabilities
  • Document machine learning architectures, workflows, configurations, testing results, and technical implementation decisions
  • Support version control, CI/CD, and other software engineering practices throughout the machine learning development lifecycle
  • Support an Agile software development lifecycle
  • Maintain awareness of emerging machine learning, model fine-tuning, federated learning, and distributed AI technologies and practices

Qualifications
Required:
  • Ability to obtain and maintain a government security clearance
  • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, or a related technical field, or equivalent relevant experience
  • 5+ years of experience in software engineering, data science, machine learning, AI engineering, or related technical disciplines, including hands-on machine learning engineering experience
  • Hands-on experience developing, training, fine-tuning, and evaluating machine learning models
  • Experience designing and implementing machine learning training and inference workflows
  • Experience with federated learning, distributed machine learning, or distributed model training concepts and architectures
  • Strong programming experience using Python and common machine learning libraries and frameworks
  • Experience with machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent technologies
  • Experience with data preprocessing, feature engineering, and model evaluation techniques
  • Experience developing and maintaining data and machine learning pipelines
  • Knowledge of model evaluation techniques, performance metrics, and validation methodologies
  • Experience integrating machine learning models and capabilities into applications or production environments
  • Understanding of distributed computing concepts and architectures
  • Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP)
  • Experience with version control systems such as Git and CI/CD practices
  • Experience troubleshooting machine learning model, pipeline, and integration issues
  • Strong analytical, problem-solving, communication, and collaboration skills

Preferred:
  • Hands-on experience implementing federated learning architectures or workflows
  • Experience with federated learning frameworks or technologies
  • Experience with large language models (LLMs), foundation models, or other generative AI technologies
  • Experience with parameter-efficient fine-tuning or other model adaptation techniques
  • Experience deploying and operating machine learning workloads in cloud environments
  • Knowledge of MLOps practices, model lifecycle management, and automated ML pipelines
  • Experience implementing machine learning solutions within controlled, secure, or restricted environments
  • Experience working within federal government or other highly regulated environments
  • Relevant cloud, machine learning, or AI certification

About steampunk
Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $115,000 to $150,000. The estimate displayed represents a typical annual salary range for this position. Annual salary is just one aspect of Steampunk's total compensation package for employees. Learn more about additional Steampunk benefits here.
Identity Statement
As part of the application process, 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.
Steampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors. Through our Human-Centered delivery methodology, we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges. If you want to learn more about our story, visit http://www.steampunk.com.
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. Steampunk participates in the E-Verify program.

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