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Machine Learning Intern Jobs in Washington, DC (NOW HIRING)

Analytica

2027 Summer Intern Associate

Bethesda, MD · Remote

$15.25 - $20.50/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 ...

SUSE RGS

Support Engineering Intern

Reston, VA · On-site

$17.50 - $22.75/hr

Support Engineering Intern Location: Remote (US Based) Objective of the Role: RGS is seeking a ... Machine Learning, or NLP * Demonstrated understanding of cloud native concepts: containers ...

ECS

Junior Software Engineer - Intern

Fairfax, VA · On-site

Everforth ECS is seeking a Junior Software Engineer Intern to work in our Fairfax, VA office for ... Machine Learning and Big Data/Cloud Solutions. The candidate works closely with the Project Manager ...

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All JobsMachine Learning Intern JobsMachine Learning Intern Jobs in Washington, DC

Machine Learning Intern information

See Washington, DC salary details

$28.9K

$48.2K

$99.7K

How much do machine learning intern jobs pay per year?

As of Jun 9, 2026, the average yearly pay for machine learning intern in Washington, DC is $48,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,800.00 and $52,100.00 per year, depending on experience, location, and employer.

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 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 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.

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 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.

More about Machine Learning Intern jobs
What are the most commonly searched types of Machine Learning jobs in Washington, DC? The most popular types of Machine Learning jobs in Washington, DC are:
What are popular job titles related to Machine Learning Intern jobs in Washington, DC? For Machine Learning Intern jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Intern jobs in Washington, DC look for? The top searched job categories for Machine Learning Intern jobs in Washington, DC are:
Machine Learning Intern jobs near you

AI Engineer Intern (USPS) - Summer 2026

LMI Consulting, LLC

Washington, DC

Other

Posted 2 days ago

Job description

AI Engineer Intern (USPS) - Summer 2026
Job Locations US-VA-Tysons | US-DC-Washington, DC
Job ID 2026-13491
# of Openings 1
Category Internships
Benefit Type Hourly Low Fringe/Intern
Overview

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors-helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

*This position is currently full-time onsite at the customers Washington DC office.

Responsibilities
    Identify opportunities where AI/ML or modeling and simulation can generate business insights or improve business processes
  • Develop and implement digital and analytic approaches
  • Work with product designers, application developers, infrastructure engineers, and other data scientists to integrate predictive and prescriptive models with web-based applications
  • Research algorithms in machine learning to identify viable approaches to meet business requirements
  • Apply machine learning methods, such as natural language processing (NLP), computer vision, regression, clustering, classification, and deep learning
  • Design solution prototypes that connect to data sources and deploy through services, such as service functions in web applications or application programming interfaces (APIs)
  • Become familiar with DevSecOps principles to continuously deliver high-quality software
  • Work with Docker to develop and deploy containerized versions of models
  • Participate in design and code reviews, and collaborate with a strong, passionate engineering team
  • Provide input to UX/UI designers and front-end application developers on how to effectively deliver model outcomes to users
  • Interface with customer stakeholders to provide technical explanations and support
Qualifications
  • Pursuit of a Bachelor's degree (Graduate student highly preferred) in engineering, mathematics, computer science, or related technical discipline required.
  • Currently enrolled in a Graduate (Masters) program highly preferred
  • Pursuing a post-graduate or undergrad degree in engineering, mathematics, computer science, modeling and simulation, operations research, or related technical discipline
  • Must be able to work for a minimum of 10-12 weeks beginning in Summer 2026 (May/June)
  • Comfortable working with agile teams, developing prototypes and functionality in short development sprints
  • Ability to work independently and collaborate effectively with a project team in an agile research and development environment
  • Comfortable using Atlassian products, including JIRA, Bamboo, Confluence, FishEye, Crucible, and Bitbucket
  • Ability to think critically to propose tractable solutions to complex problems
  • Effective written and verbal communication skills
  • Ability to communicate complex concepts to both technical and business-focused audiences
  • Familiarity or desire to excel with modern programming languages appropriate for machine learning prototyping; Python is preferred, but experience with other languages such as Java, C++, C#, JavaScript and R demonstrate the necessary ability
  • Familiarity with the underlying mathematics of machine learning
  • Knowledge of data structures and data management principles, methods, and tools
  • Desire to explore machine learning frameworks and libraries, such as scikit-learn, TensorFlow, and Spark ML
  • Ability to work with integrated development environments, such as Jupyter, JupyterLab, JetBrains IntelliJ IDEA, JetBrains PyCharm, JetBrains CLion, and Visual Studio Code
  • Ability to collaborate with a team that develops applications using web development frameworks, such as Angular (1.x/2+), React, and Ember, and server frameworks, such as Node.js and Express.js
  • Ability to consume or interface with cloud computing and storage services, including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud
  • Familiarity or desire to become familiar with containerization technologies, such as Docker, Kubernetes, Amazon Elastic Container Service (ECS), and Amazon Elastic Kubernetes Service (EKS)

Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.


LMI is an Equal Opportunity Employer. LMI is committed to the fair treatment of all and to our policy of providing applicants and employees with equal employment opportunities. LMI recruits, hires, trains, and promotes people without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, disability, age, protected veteran status, citizenship status, genetic information, or any other characteristic protected by applicable federal, state, or local law. If you are a person with a disability needing assistance with the application process, please contact accommodations@lmi.org
Colorado Residents: In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.
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