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Embedded Machine Learning Internship Jobs in Severn, MD

Mixpeek

Machine Learning Engineer

Washington, DC · On-site

$180 - $240/hr

  • Medical

  • Retirement

  • PTO

The Machine Forward Deployed Learning Engineer position requires a mix of software development, LLM ... Experience in a customer-facing or embedded delivery role. * Exposure to federated or privacy ...

New

Crowe LLP

Machine Learning Intern

Washington, DC

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

Crowe LLP

Machine Learning Intern

Washington, DC

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

Xometry

Staff Machine Learning Engineer

North Bethesda, MD · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... Xometry's embedded DFM AI + IQE integration with Teamcenter and Designcenter. You will be ... machine learning engineering, with a track record of owning and delivering complex ML systems in ...

Xometry

Staff Machine Learning Engineer

North Bethesda, MD

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... Xometry's embedded DFM AI + IQE integration with Teamcenter and Designcenter. You will be ... machine learning engineering, with a track record of owning and delivering complex ML systems in ...

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All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Internship JobsEmbedded Machine Learning Internship Jobs in Severn, MD

Embedded Machine Learning Internship information

See Severn, MD salary details

$28.3K

$47.3K

$97.8K

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

As of Aug 18, 2026, the average yearly pay for embedded machine learning internship in Severn, MD is $47,339.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,100.00 and $51,100.00 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 cities near Severn, MD are hiring for Embedded Machine Learning Internship jobs?

Cities near Severn, MD with the most Embedded Machine Learning Internship job openings:

Embedded Machine Learning Internship jobs near you
Infographic showing various Embedded Machine Learning Internship job openings in Severn, MD as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $47,339 per year, or $22.8 per hour.

Machine Learning Engineer

Mixpeek

Washington, DC • On-site

$180 - $240/hr

Other

Medical, Retirement, PTO

Posted yesterday

New

Job description

About Adelphi

Adelphi's Vision is to build the biggest AI Deployment company for National Security, which requires talent that is extremely good at problem solving, gets excited about National Security challenges, and thrives in software factories. We're executing a Mission that (1) Identifies the core bottlenecks in Warfighting, Intelligence and the Enterprise, (2) Assigns top talent with backgrounds in systems and machine learning engineering, and (3) Finds repeatability in solution development to target similar offices across the DoW/IC. The business has 10x'd in under two years and has built trust with the senior most leaders at the Department of War and Intelligence Community.

About the Role:

The Machine Forward Deployed Learning Engineer position requires a mix of software development, LLM Ops, and SecDevOps practices, resulting in an exciting, fast-paced engineering role. This role requires the ability to contribute to solutions across the full LLM stack, from the OS, storage, and network up to the API and transport layer. Experience in the defense or intelligence fields is required. You will contribute to end-to-end delivery of agentic, full-stack systems built on top of frontier models, from first prototype to stable production, embedded alongside our defense and intelligence customers.

Location:

This role is based in the DC/Metro area; remote candidates will be considered with 25% travel expected.

Clearance Requirement:

An active U.S. Government clearance is strongly preferred, but we are open to clearance eligible candidates.

Is this you?

We are an AI-native engineering team. We expect every engineer to leverage LLMs and AI tooling as a core part of how they design, build, ship, and operate agentic systems that turn frontier-model capability into mission outcomes.

  • You use AI coding tools (Claude Code, Cursor, Copilot) daily and instinctively.

  • You leverage LLMs across the development lifecycle, and stay current with emerging models and tooling.

  • You have working knowledge of modern agent frameworks and SDKs (LangGraph, OpenAI Agents SDK, Claude Agent SDK, AutoGen, or similar).

  • Familiarity with MCP or similar LLM integration frameworks.

  • You have a clear-eyed view of AI limitations. You know when to trust AI-generated output and when to verify.

Expectations:

  • Contribute to end-to-end delivery of agentic, full-stack systems from prototype to production, embedded alongside defense and intelligence customers.

  • Build and deploy ML services leveraging LLMs, embeddings, RAG, and agent orchestration into production environments, including classified and air-gapped ones.

  • Work directly with customers to understand problems, support delivery sequencing, and ship AI applications under real-world constraints.

  • Help codify repeatable patterns into reusable tools and building blocks that help the team ship faster.

Bonus Points:

  • Familiarity with infrastructure management (Docker, Kubernetes, AWS).

  • Exposure to encryption, authentication, Linux systems administration, DevOps, or SRE.

  • Any production experience with agentic services or forward-deployed AI applications.

  • Experience in a customer-facing or embedded delivery role.

  • Exposure to federated or privacy-preserving data architectures.

Benefits:

  • Healthcare coverage: 100% employee premium and 50% dependents premium coverage of a platinum-level plan.

  • 401K with 2% company match.

  • Equity in a seed-stage business.

  • Access to 6713 Club - a members-only club in McLean, VA.

  • $500 monthly Physical and Mental Health reimbursement program.

  • Flexible PTO policy.

  • Competitive salary and equity compensation.

  • Opportunity to work on impactful projects in the national security sector.

  • Career growth and leadership opportunities in a dynamic, innovative environment.

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