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Embedded Machine Learning Engineer Jobs (NOW HIRING)

MORSE Corp

Machine Learning Engineer

Arlington, VA · On-site

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role ... embedded system. You will be part of our team working to accelerate our US National Security ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered ... shared AI platform and embedded across products- Design, build, and own end-to-end GenAI ...

MORSE Corp

Machine Learning Engineer

Cambridge, MA · On-site

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role ... embedded system. You will be part of our team working to accelerate our US National Security ...

ExtendMyTeam

Machine Learning Engineer

Cary, NC

Position Summary We are seeking a Machine Learning Engineer to help design, deploy, and support production machine learning systems within a collaborative engineering organization. This individual ...

Heven AeroTech

Machine Learning Engineer

Sterling, VA · On-site

Machine Learning Engineer Company: Heven AeroTech Location: Sterling, Virginia FLSA: Exempt About ... Embedded Linux and ROS experience * Defense/aerospace industry background * Additional Google Cloud ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

PROPRIUS

Senior Machine Learning Engineer

New York, NY

$114.30K - $157K/yr

Sr. Machine Learning Engineer Location: New York, NY Sponsorship: Yes Relocation: Yes Industry ... with machine learning in embedded applications: model quantization, fixed point neural networks ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

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Embedded Machine Learning Engineer information

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$70K

$153.4K

$174K

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

As of May 30, 2026, the average yearly pay for embedded machine learning engineer in the United States is $153,383.00, 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 are the key skills and qualifications needed to thrive as an Embedded Machine Learning Engineer, and why are they important?

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 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 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.

More about Embedded Machine Learning Engineer jobs
What cities are hiring for Embedded Machine Learning Engineer jobs? Cities with the most Embedded Machine Learning Engineer job openings:
What states have the most Embedded Machine Learning Engineer jobs? States with the most job openings for Embedded Machine Learning Engineer jobs include:
What job categories do people searching Embedded Machine Learning Engineer jobs look for? The top searched job categories for Embedded Machine Learning Engineer jobs are:
Embedded Machine Learning Engineer jobs near you
Infographic showing various Embedded Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 92% Physical, and 8% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.
Machine Learning Engineer

Machine Learning Engineer

MORSE Corp

Arlington, VA • On-site

Other

Posted 24 days ago

Job description

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms. MORSE's AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE's current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 
  • Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  
  • Use MLOps tools for efficient experiment tracking, data management, and reproducibility 
  • Write robust, efficient, and maintainable code 
  • Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 
  • Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 
  • US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance 
  • Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 
  • Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 
  • Proven experience testing and validating the performance of AI technologies in real-world applications 
  • Proficiency in Python 
  • Experience with cloud platforms (AWS and Azure) 
  • Experience with Docker 
  • Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 
  • Exceptional communication skills and the ability to work well with customers 
  • Understanding of Department of Defense requirements and standards is a plus 

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