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Machine Learning Summer Intern Jobs in Washington, DC

Crowe LLP

Machine Learning Intern

Washington, DC · On-site

$27 - $42/hr

... academic summer. DS interns will have a designated data scientist mentor and will spend the ... To that end, there are three major components with which an intern should expect to engage.

Crowe LLP

Machine Learning Intern

Washington, DC · On-site

$27 - $42/hr

... academic summer. DS interns will have a designated data scientist mentor and will spend the ... To that end, there are three major components with which an intern should expect to engage.

Analytica

2027 Summer Intern Associate

Bethesda, MD · On-site +1

$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 ...

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 ...

Canvas

Engineering ( Summer Intern)

Arnold, MD · On-site

$16.25 - $21.25/hr

Engineering (Summer Intern) Location : Tullahoma, TN- Arnold AFB Canvas is accepting resumes for ... This internship provides a hands-on learning experience directly related to responsibilities that ...

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

Machine Learning Summer Intern information

See Washington, DC salary details

$28.9K

$48.2K

$99.7K

How much do machine learning summer intern jobs pay per year?

As of Aug 22, 2026, the average yearly pay for machine learning summer 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 is a machine learning summer intern?

Machine Learning Summer Interns are students or recent graduates who work temporarily at a company, usually during the summer, to gain practical experience in machine learning. They typically assist with data analysis, model development, and research tasks under the supervision of experienced data scientists or engineers. This role allows interns to apply their academic knowledge to real-world problems, learn industry tools and workflows, and build professional networks. Internships often serve as a stepping stone to full-time positions in machine learning or related fields.

What types of projects does a machine learning summer intern typically work on?

Machine Learning Summer Interns often work on focused projects such as data preprocessing, developing and testing machine learning models, or contributing to research and prototyping efforts. These projects are designed to provide practical experience while directly supporting the team's ongoing initiatives, such as improving model accuracy or automating data pipelines. Interns usually collaborate closely with data scientists and engineers, gaining mentorship and exposure to real-world problem-solving. This hands-on involvement helps interns understand the end-to-end process of deploying machine learning solutions and prepares them for future roles in the field.

What are the key skills and qualifications needed to thrive as a machine learning summer intern?

To thrive as a Machine Learning Summer Intern, you need a solid understanding of programming (especially Python), foundational knowledge of machine learning concepts, and coursework or experience in statistics and mathematics. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is typically expected. Strong problem-solving abilities, eagerness to learn, and effective communication skills help you collaborate and adapt in a fast-paced research or development setting. These abilities are crucial for contributing to real-world projects, learning from experienced mentors, and building a foundation for a future career in machine learning.

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

AspectMachine Learning Summer InternData Science Summer Intern
Required CredentialsUndergraduate or graduate in CS, AI, or related fields; some experience in ML frameworksUndergraduate or graduate in statistics, CS, or related fields; experience in data analysis
Work EnvironmentDeveloping ML models, algorithms, and prototypes in tech or research companiesAnalyzing datasets, creating reports, and supporting data-driven decisions in various industries
Employer & Industry UsageTech companies, AI startups, research labsFinance, healthcare, marketing, and tech firms

While both roles involve working with data, Machine Learning Summer Interns focus on developing algorithms and models, whereas Data Science Summer Interns analyze data to generate insights. The roles often overlap but differ mainly in technical focus and project scope.

What are the most commonly searched types of Machine Learning Summer jobs in Washington, DC?

The most popular types of Machine Learning Summer jobs in Washington, DC are:

Machine Learning Summer Intern jobs near you
Infographic showing various Machine Learning Summer Intern job openings in Washington, DC as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $48,230 per year, or $23.2 per hour.

Data Scientist & Machine Learning Engineer Intern

DMS International

Silver Spring, MD • On-site, Remote

Part-time, Internship

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

Job description

Data Management Services, Inc. (DMS International) is a professional services firm headquartered in Silver Spring, Maryland, with work locations throughout the continental United States. We prepare managers and executives to lead their workforce through customized learning solutions that drive the standards of an ever-changing world. We build creative, unique, and engaging learning experiences for commercial, civilian and defense organizations. Our high-caliber talent, delivery methodology and innovative solutions contribute to preparing a workforce that is ready for the future. You can join us on this journey to bring efficiency and creativity to our customers.
At DMS, we are the catalyst for effective workforce transformation. To achieve this, we hire professionals who take pride in doing quality work and who are excited about contributing to the professional development of tomorrow's leaders.
DMS seeks candidates that possess and display the attributes that reflect our Core Values of:
  • Quality in delivering solutions
  • Leadership
  • Teamwork
  • Innovation
  • Integrity in conduct
  • Responsiveness to our customer's mission.

DMS International is an Equal Opportunity Employer. We make employment decisions without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, pregnancy, childbirth, lactation and related medical conditions, genetic factors, military/veteran status, or other characteristics protected by law. We encourage individuals from all backgrounds to apply.
Job Description
DMS is seeking a Data Scientist & Machine Learning Engineer Intern to join our technical team. The intern will support the design, development, testing, and implementation of AI-powered products for content creation, learning, training, simulations, and decision support. Working under the supervision of the AI and Simulation Program Manager, the intern will collaborate with developers, instructional designers, simulation specialists, and subject matter experts to transform data and emerging AI technologies into practical applications.
Responsibilities
  • Support the development of Generative AI and Large Language Model (LLM) applications, including prompt engineering and Retrieval-Augmented Generation (RAG)
  • Develop AI capabilities for transforming source documents into courses, learning content, assessments, scenarios, case studies, and other digital content
  • Assist in developing AI-powered simulations and serious games, including dynamic scenarios, intelligent agents, participant analytics, and after-action reports
  • Collect, clean, analyze, and visualize structured and unstructured data
  • Develop natural language processing (NLP) solutions for document summarization, semantic search, classification, information extraction, and question answering
  • Build prototypes and integrate AI/ML models with applications through APIs and cloud services
  • Conduct model testing and evaluation for performance, accuracy, reliability, bias, and hallucinations
  • Support responsible AI practices, model documentation, data governance, and AI risk management
  • Develop, train, test, and evaluate machine learning and predictive models
  • Research emerging technologies such as agentic AI, multimodal AI, synthetic data, digital twins, knowledge graphs, and adaptive learning

Required Skills & Experience
  • Familiarity with machine learning frameworks such as Scikit-learn, PyTorch, and/or TensorFlow
  • Knowledge of Generative AI concepts, LLMs, prompt engineering, embeddings, RAG, and/or Hugging Face
  • Familiarity with REST APIs, Git/GitHub, and basic application development
  • Knowledge of statistical analysis, data visualization, and predictive modeling
  • Strong analytical and problem-solving skills
  • Curiosity about emerging AI technologies and willingness to experiment and learn
  • Ability to work independently and collaboratively within a multidisciplinary team
  • Experience through academic projects, research, hackathons, personal projects, or internships involving machine learning, Generative AI, NLP, simulations, analytics, or AI application development is preferred
  • GitHub portfolio or examples of AI/ML projects are encouraged
  • Experience or coursework in Python, SQL, Pandas, NumPy, and Jupyter Notebook
  • Exposure to OpenAI, Azure OpenAI, IBM watsonx, AWS/GCP AI services, LangChain, LlamaIndex, vector databases, FastAPI, Django, Flask, or Docker is a plus.

Education
  • Currently pursuing or recently completed a Bachelor's, Master's, or doctoral degree in Computer Science, Data Science, Artificial Intelligence/Machine Learning, Statistics, Applied Mathematics, Computer or Software Engineering, Information Systems, Operations Research, or a related quantitative or technical field

Position Type
  • Part-time Intern

Location
  • Remote

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