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Embedded Machine Learning Engineer Jobs in Herndon, VA

Mixpeek

Machine Learning Engineer

Washington, DC · On-site

$180 - $240/hr

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

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 ...

Adelphi

Machine Learning Engineer

Washington, DC · On-site

$150 - $210/hr

About the Role The Machine Forward Deployed Learning Engineer position requires a mix of software ... Experience in a customer‑facing or embedded delivery role. * Exposure to federated or ...

Cymertek Corporation

Machine Learning Engineer

Reston, VA · On-site

$110 - $170/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 ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

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 ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Herndon, VA

Embedded Machine Learning Engineer information

See Herndon, VA salary details

$72K

$157.7K

$178.9K

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

As of Aug 19, 2026, the average yearly pay for embedded machine learning engineer in Herndon, VA is $157,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $135,200.00 and $177,900.00 per year, depending on experience, location, and employer.

What does an embedded machine learning engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What are the key skills and qualifications needed to thrive as an embedded machine learning engineer?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by embedded machine learning engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Herndon, VA?

For Embedded Machine Learning Engineer jobs in Herndon, VA, the most frequently searched job titles are:

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Cities near Herndon, VA with the most Embedded Machine Learning Engineer job openings:

Embedded Machine Learning Engineer jobs near you

Machine Learning Engineer

Mixpeek

Washington, DC • On-site

$180 - $240/hr

Other

Medical, Retirement, PTO

Posted 2 days ago

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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