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Embedded Machine Learning Internship Jobs in Washington, DC

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Parsons

Machine Learning / Data Scientist

Washington, DC

$88K - $154K/yr

The Machine Learning / Data Scientist is a hands-on practitioner with strong capabilities in model ... Familiarity with integrating model outputs into BI tools or applications (e.g., via APIs, embedded ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Mclean, VA

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Sr. Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

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All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Internship JobsEmbedded Machine Learning Internship Jobs in Washington, DC

Embedded Machine Learning Internship information

See Washington, DC salary details

$28.9K

$48.2K

$99.7K

How much do embedded machine learning internship jobs pay per year?

As of Jul 29, 2026, the average yearly pay for embedded machine learning internship 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 an Embedded Machine Learning Internship?

An Embedded Machine Learning Internship is a temporary position designed for students or recent graduates to gain hands-on experience in developing and deploying machine learning algorithms on embedded systems. These internships typically involve working with hardware such as microcontrollers, sensors, or edge devices, and using specialized tools to optimize machine learning models for low-power and resource-constrained environments. Interns collaborate with engineers and data scientists to create efficient, real-world AI solutions that run directly on devices rather than relying on cloud computing. This role helps bridge the gap between theoretical machine learning concepts and practical implementation on embedded platforms.

What are some typical projects or tasks I might work on during an Embedded Machine Learning Internship?

During an Embedded Machine Learning Internship, you can expect to work on projects such as optimizing machine learning models to run efficiently on hardware with limited resources, integrating AI algorithms into embedded systems (like microcontrollers or IoT devices), and performing real-time data processing. You'll likely collaborate closely with software engineers and hardware designers to test models on physical devices, debug performance issues, and contribute to documentation. These experiences provide practical exposure to the challenges of deploying AI in real-world, resource-constrained environments and help build skills valuable for a future career in embedded AI.

What are the key skills and qualifications needed to thrive as an Embedded Machine Learning Intern, and why are they important?

To thrive as an Embedded Machine Learning Intern, you need a background in computer science, electrical engineering, or a related field with strong programming skills in C/C++ and Python, as well as foundational knowledge of machine learning algorithms. Experience with embedded systems development tools (such as ARM Cortex, Raspberry Pi, or Arduino), version control systems, and familiarity with ML frameworks like TensorFlow Lite or Edge Impulse is often required. Analytical thinking, problem-solving ability, and effective teamwork are vital soft skills for success in this role. These skills and qualities are crucial for efficiently developing, optimizing, and deploying machine learning solutions on resource-constrained embedded platforms.
What are the most commonly searched types of Embedded Machine Learning jobs in Washington, DC? The most popular types of Embedded Machine Learning jobs in Washington, DC are:
What are popular job titles related to Embedded Machine Learning Internship jobs in Washington, DC? For Embedded Machine Learning Internship jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning Internship jobs in Washington, DC look for? The top searched job categories for Embedded Machine Learning Internship jobs in Washington, DC are:
Embedded Machine Learning Internship jobs near you
Infographic showing various Embedded Machine Learning Internship job openings in Washington, DC as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $48,230 per year, or $23.2 per hour.

Machine Learning Engineer

Nastech Global

Fort Belvoir, VA • On-site

Contractor

Posted yesterday

Job description

Job Title:  Machine Learning Engineer
Location: Fort Belvoir, VA (5 days onsite)
Duration:  Long-Term Contract
Citizenship: US Citizen with active TS/SCI w CI Poly
 
Top Required Skills
AWS, ML/AI Development, Python or Scala, or Java, TS/SCI w CI Poly willing to work onsite in Ft. Belvoir
 
Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
Proven track record in designing, building, and/or delivering ML models and components that solve real-world business problems, while working in collaboration with other technical teams.
Collaborate as part of a cross-functional Agile team to create and enhance capabilities that enable state-of-the-art big data and ML applications.
Retrain, maintain, and monitor models in production.
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
Be a trusted advisor to the Government to ensure all third-party vendors' platforms and code delivered are “fit for purpose”
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and
Use programming languages like Python, Scala, or Java.
Ability to mentor and coach junior resources with delivery tasks.
Self-motivated, with the ability to work effectively both independently and in a team environment
 
Thanks and Regards,
Murali Sharma
202-828-3494
Murali@NasTechglobal.com