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Executive Full Stack Machine Learning Engineer Jobs in Ellicott City, MD

Mixpeek

Machine Learning Engineer

Washington, DC · On-site

$200 - $250/hr

The Machine Forward Deployed Learning Engineer position requires a mix of software development, LLM ... This role requires the ability to contribute to solutions across the full LLM stack, from the OS ...

Cymertek Corporation

Machine Learning Engineer

Reston, VA · On-site

$125 - $150/hr

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

AISquared

Machine Learning Engineer

Washington, DC · On-site

Job Summary : aisquared is a company focused on AI solutions, and they are seeking a highly skilled Machine Learning Engineer to join their core AI team. In this role, you will be responsible for ...

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All JobsFull Stack Machine Learning Engineer JobsExecutive Full Stack Machine Learning Engineer JobsExecutive Full Stack Machine Learning Engineer Jobs in Ellicott City, MD

Executive Full Stack Machine Learning Engineer information

See Ellicott City, MD salary details

$44.3K

$134.3K

$189.8K

How much do executive full stack machine learning engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for executive full stack machine learning engineer in Ellicott City, MD is $134,279.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,600.00 and $157,400.00 per year, depending on experience, location, and employer.

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Executive Full Stack Machine Learning Engineer jobs near you
Infographic showing various Executive Full Stack Machine Learning Engineer job openings in Ellicott City, MD as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $134,279 per year, or $64.6 per hour.

Machine Learning Engineer

Mixpeek

Washington, DC • On-site

$200 - $250/hr

Other

Medical, Retirement, PTO

Posted 21 days ago

Key responsibilities

  • Contribute to the end-to-end delivery of agentic, full-stack systems built on frontier models, from prototype to stable production.

  • 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.

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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