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Embedded Machine Learning Jobs (NOW HIRING)

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 ...

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 ...

HealthEdge

Machine Learning Engineer

Overview Machine Learning Engineer, AI Platform As a Machine Learning Engineer, you will design ... Experience working directly with non-technical stakeholders or in embedded/consulting-style ...

HealthEdge

Machine Learning Engineer

Overview Machine Learning Engineer, AI Platform As a Machine Learning Engineer, you will design ... Experience working directly with non-technical stakeholders or in embedded/consulting-style ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

... shared AI platform and embedded across products- Design, build, and own end-to-end GenAI ... machine learning concepts, including supervised and unsupervised learning; exposure to ...

TetraMem Inc

Senior Machine Learning Engineer

San Jose, CA · On-site

$200K - $280K/yr

Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions ... Strong hands-on experience in machine learning, with a focus on edge AI, on-device inference, and ...

Actalent

Sr. Staff Embedded AI Engineer

Columbia, MD

$122.10K - $160K/yr

Integrate machine learning frameworks such as TensorFlow and PyTorch into the model translation and ... Strong foundation in embedded engineering using C and C++. * Robust mathematical background ...

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site +1

About the Team You'll lead the Machine Learning and FPT teams, working closely with the Director of ... Edge ML deployment experience (ONNX, TensorRT, mobile/embedded inference) * Familiarity with ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

$181.10K - $272.10K/yr

... shared AI platform and embedded across products - Design, build, and own end-to-end GenAI ... machine learning concepts, including supervised and unsupervised learning; exposure to ...

PROPRIUS

Senior Machine Learning Engineer

New York, NY · On-site

$114.30K - $157K/yr

Expert level coding skills (Python, C++ at minimum) * 3+ years' experience working with machine learning in embedded applications: model quantization, fixed point neural networks (CNN and RNN)

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How much do embedded machine learning jobs pay per year?

As of Jun 4, 2026, the average yearly pay for embedded machine learning 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 is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in the Embedded Machine Learning position, and why are they important?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.
More about Embedded Machine Learning jobs
What cities are hiring for Embedded Machine Learning jobs? Cities with the most Embedded Machine Learning job openings:
What are the most commonly searched types of Embedded Machine Learning jobs? The most popular types of Embedded Machine Learning jobs are:
What states have the most Embedded Machine Learning jobs? States with the most job openings for Embedded Machine Learning jobs include:
What job categories do people searching Embedded Machine Learning jobs look for? The top searched job categories for Embedded Machine Learning jobs are:
Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in the United States as of May 2026, with employment types broken down into 1% Locum Tenens, 4% Internship, 62% Full Time, 31% Part Time, 1% Temporary, and 1% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% 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

Cambridge, MA • On-site

Other

This job post has expired today. Applications are no longer accepted.

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 

Apply