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Embedded Machine Learning Engineer Jobs in Manassas, VA

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 ...

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 ...

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 ...

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 ...

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 ...

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Embedded Machine Learning Engineer information

See Manassas, VA salary details

$70K

$153.3K

$174K

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

As of Sep 1, 2026, the average yearly pay for embedded machine learning engineer in Manassas, VA is $153,349.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 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 Manassas, VA?

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

What job categories do people searching Embedded Machine Learning Engineer jobs in Manassas, VA look for?

The top searched job categories for Embedded Machine Learning Engineer jobs in Manassas, VA are:

What cities near Manassas, VA are hiring for Embedded Machine Learning Engineer jobs?

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

Infographic showing various Embedded Machine Learning Engineer job openings in Manassas, VA as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 25% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $153,349 per year, or $73.7 per hour.

Machine Learning Engineer - Autonomy

Heven AeroTech

Sterling, VA โ€ข On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago


Job description

Title: Machine Learning Engineer, Autonomy
Company: Heven AeroTech
Location: Bingen, Washington or Sterling, Virginia
FLSA:ย Exempt

About Our Company:

At Heven AeroTech (Heven), we don't just believe in the power of people-we build our success on it. As a recognized leader in hydrogen-powered drones, we've earned recognition for creating a workplace where innovation thrives, collaboration is second nature, and every employee feels valued. Our culture is anchored in trust and a shared commitment to excellence.

We believe great teams are built on individuals who are humble, hungry, and smart-those who put team success first, take initiative to continuously improve, and demonstrate strong interpersonal awareness. At Heven, your voice matters, your ideas are heard, and your contributions make a tangible impact as you grow through hands-on experience and collaboration across the team.

Role Summary:
Reporting to the Head of Mission Systems and Software, the Machine Learning Engineer - Autonomy develops and deploys machine learning and autonomy capabilities for Heven AeroTech uncrewed aircraft systems. The role focuses on practical UAS autonomy, including perception, tracking, sensor fusion, mission-level decision making, planning, and integration with flight-control, mission-system, onboard-compute, and payload interfaces. This engineer works closely with other Machine Learning Engineers, Platform Engineers, Flight Test, and aircraft engineering teams to take autonomy capabilities from development through simulation, integration, ground test, and flight test.

Essential Responsibilities:

  • Develop, integrate, and deploy machine learning and autonomy capabilities for uncrewed aircraft, with emphasis on reliable operation on real aircraft and onboard compute.
  • Develop mission-level autonomous behaviors using appropriate combinations of state machines, behavior trees, planners, optimization methods, deterministic logic, and machine learning.
  • Develop and integrate perception capabilities including object detection, classification, tracking, scene understanding, sensor fusion, and geospatial reasoning.
  • Integrate autonomy software with autopilots, companion computers, mission computers, sensors, payloads, data links, and GCS/C2 systems while maintaining clear interfaces with flight-control functions.
  • Develop production-quality C++ and Python software for real-time and near-real-time execution, including optimization for NVIDIA GPU and embedded edge-compute platforms.
  • Develop and use simulation, SIL, HIL, bench-test, and automated test environments to evaluate autonomy behavior and reduce risk prior to flight.
  • Support aircraft integration, ground test, and flight test of autonomy capabilities, including analysis of logs and test data to characterize performance and drive improvements.
  • Collaborate across Heven AeroTech with Machine Learning Engineers, Platform Engineers, Flight Test, avionics, electrical, mechanical, and other engineering teams.

Qualifications & Experience:

Required:

  • BA/BS degree in Computer Science, Electrical Engineering, Robotics, Aerospace Engineering, or a related technical field, or equivalent practical experience.
  • 2-5 years of experience developing and deploying machine learning or autonomy software on robotic, autonomous, or UAS platforms.
  • Strong C++ and Python development skills, including Linux-based development and modern machine learning frameworks.
  • Working knowledge of perception, sensor integration, autonomous decision making or planning, and real-time system integration.
  • Professional working proficiency in English (spoken and written) is required to perform the responsibilities of this role.

Preferred:

  • Direct experience with UAS autonomy, aircraft integration, or flight test.
  • Experience with NVIDIA edge compute, CUDA/TensorRT, ROS 2, MAVLink, or comparable robotics and vehicle interfaces.
  • Aerospace or defense experience and eligibility to obtain a DoD Secret clearance.

Physical Requirements:

  • Ability to work effectively in a standard office, engineering laboratory, aircraft integration, hangar, and outdoor flight-test environment.
  • Ability to stand, walk, bend, kneel, reach, and work around aircraft, ground-support equipment, test equipment, and computing hardware for extended periods as required.
  • Ability to lift, carry, and position equipment and components weighing up to 25 pounds, with or without reasonable accommodation.
  • Ability to safely work in outdoor environments and varying weather conditions during ground and flight-test activities.
  • Ability to work around aircraft systems, electrical equipment, rotating equipment, batteries, and other laboratory/flight-test hazards while following applicable safety procedures and PPE requirements.
  • Ability to visually inspect equipment, read computer displays, instrumentation, schematics, logs, and test data, with or without reasonable accommodation.
  • Ability to work flexible hours, including early mornings, evenings, or occasional weekends, when required to support aircraft integration, ground testing, or flight-test operations.
  • Ability and willingness to travel to company facilities, customer sites, and/or designated flight-test locations as required by the position.

Benefits Overview:ย 
Heven AeroTech offers a competitive benefits package designed to support the health, financial security, and overall well-being of our employees and their families. Benefits include medical, dental, and vision coverage, retirement plans, paid time off/sick, and additional protections such as critical illness, hospital indemnity, accident coverage, and short- and long-term disability.

Equal Employment Opportunity Statement:ย 
Heven AeroTech is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic under applicable law.