Machine Learning Intern Jobs in Washington, DC
Machine Learning Intern jobs in Washington, District of Columbia are in active demand, concentrated in the Capitol Riverfront, NoMa, and Foggy Bottom corridors across federal contractors, defense tech, and research-driven organizations. Employers hiring right now include Booz Allen Hamilton, Adelphi, and Anduril. See the openings below and apply to the ones that match your experience.
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About Adelphi: Adelphi builds AI/ML-enabled secure data access and sharing technology for the U.S. intelligence and defense communities, using its Connector software product to enable federated data discovery that cuts intelligence-sharing time from months to minutes. The company's mission is to eliminate data silos, build trust in automation without compromising security, and improve information flow across mission-critical environments. Adelphi closed a $7M Seed round in August 2025 and has Customers across the Intelligence Community and the Department of War.
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.
$500 monthly Physical and Mental Health reimbursement program.
Unlimited time-off 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.
About Adelphi: Adelphi builds AI/ML-enabled secure data access and sharing technology for the U.S. intelligence and defense communities, using its Connector software product to enable federated data discovery that cuts intelligence-sharing time from months to minutes. The company's mission is to eliminate data silos, build trust in automation without compromising security, and improve information flow across mission-critical environments. Adelphi closed a $7M Seed round in August 2025 and has Customers across the Intelligence Community and the Department of War.
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.
$500 monthly Physical and Mental Health reimbursement program.
Unlimited time-off 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.
See All 15 Machine Learning Intern Jobs in Washington
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Machine Learning Intern Jobs in Washington: Frequently Asked Questions
How do I get a machine learning intern job in Washington?
Washington's machine learning intern market is shaped by its concentration of federal agencies, defense contractors, and policy-adjacent research institutions, so candidates who can work with structured government datasets or demonstrate security-clearance eligibility stand out. Focus your search on the NoMa, Capitol Riverfront, and Foggy Bottom corridors where tech-forward employers cluster. Strong Python skills, experience with natural language processing or computer vision, and any prior federal or academic research project give you a real edge here.
Which companies hire machine learning interns in Washington?
Employers hiring machine learning interns in Washington right now include Booz Allen Hamilton, Adelphi, and Anduril, based on current listings on Migrate Mate as of July 2026. Washington's hiring mix is distinctive, leaning heavily toward defense contractors, federal consulting firms, and mission-driven research organizations alongside a growing base of commercial tech companies.
Are there remote machine learning intern jobs in Washington?
Yes, though availability depends on the role, since positions involving classified systems or on-site lab work are rarely remote, while data analysis and model development tasks are frequently offered remotely. About 50% of machine learning intern openings tied to Washington are remote or hybrid as of July 2026, reflecting the city's mix of secure and desk-based work. Model training, literature review, and pipeline development are the tasks most commonly performed off-site.
How can I get a machine learning intern job in Washington with little or no experience?
The most realistic entry path in Washington is through university research partnerships and federally funded programs, since agencies and contractors in the area regularly recruit interns directly from nearby schools like Georgetown, George Washington University, and the University of Maryland. Look for research assistant or data analyst intern roles at think tanks and consulting firms as lateral entry points. A personal project involving public government datasets strengthens any application significantly in this market.
Which industries hire the most machine learning interns in Washington?
Washington machine learning intern roles concentrate in Technology & Software, Construction & Real Estate, and Consulting & Professional Services, based on current listings on Migrate Mate as of July 2026. Washington's role as the seat of federal government drives unusually high demand from defense, intelligence, and public policy sectors, which rely on machine learning interns for data processing, predictive modeling, and research support.
Related Jobs in District of Columbia
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