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Machine Learning Intern Jobs in Washington (NOW HIRING)

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 ...

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Machine Learning Intern information

See Washington salary details

$28.9K

$48.2K

$99.7K

How much do machine learning intern jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning intern in Washington 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 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 Washington?

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

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

What job categories do people searching Machine Learning Intern jobs in Washington look for?

The top searched job categories for Machine Learning Intern jobs in Washington are:

What cities in Washington are hiring for Machine Learning Intern jobs?

Cities in Washington with the most Machine Learning Intern job openings:

Machine Learning Intern jobs near you
Infographic showing various Machine Learning Intern job openings in Washington as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 21% Part Time, and 2% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $48,230 per year, or $23.2 per hour.

AI/ML 2 (FST - 118)

Annapolis Junction, MD • On-site

SageCor Solutions
See more jobs at SageCor Solutionsexternal

Full-time

Re-posted 15 days ago

Job description

Serving Maryland and the Greater Washington D.C. area, SageCor Solutions (SageCor) is a growing company bringing complete engineering services and true full lifecycle System Engineering services to areas requiring (or desiring) nationally-recognized expertise in high performance computing, large data analytics and cutting edge information technologies.

Active TS/SCI w/ Polygraph required.

Required Experience:

Five (5) years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required. A Master's or Ph.D. degree in advanced math, artificial intelligence, data science, computer science or deep learning from an accredited college or university. 5 additional years of machine learning experience with a relevant Bachelor's degree may be substituted for a Master's degree. Experience with standard machine language frameworks, e.g. Pytorch, TensorFlow.

Optional Skills:

Expert knowledge of multiple programming languages, e.g. Python, Java, C, R.

Consistent with federal and state law where SageCor conducts business, SageCor Solutions provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, or any other protected class.

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