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Embedded Machine Learning Internship Jobs in Massachusetts

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 ...

GN Group

Machine Learning Engineer - Edge

Lowell, MA · On-site +1

$86K - $135K/yr

Machine Learning Engineer - Edge *Please consider before applying: This is a hybrid role, and ... Experience with embedded systems and hardware platforms. * Fundamentals of audio and speech signal ...

Cognex

Senior Machine Learning Engineer

Natick, MA · On-site

$115K - $225K/yr

Cognex is a global leader in the exciting and growing field of machine vision. Our employees ... The team works across custom hardware, optimized embedded systems, and nextgeneration algorithm ...

Motional

Senior Embedded Software Engineer

Boston, MA · On-site +1

$134.70K - $176.50K/yr

... machine learning, sensors, and hardware compute platforms to evolve Motional's next-generation on ... If you are a software engineer and love the idea of working on embedded AI hardware and software ...

Amazon

Machine Learning Engineer, Alexa AI

Boston, MA · On-site

The Alexa AI team is looking for a passionate, talented, and inventive Machine Learning Engineer ... BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ ...

MORSE Corp

Machine Learning Engineer

Cambridge, MA · On-site

$90K - $210K/yr

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 ...

ASUS

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global ... Optimize models for real-time performance on embedded and edge computing platforms. * Build and ...

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Embedded Machine Learning Internship information

What are the key skills and qualifications needed to thrive as an Embedded Machine Learning Intern, and why are they important?

To thrive as an Embedded Machine Learning Intern, you need a background in computer science, electrical engineering, or a related field with strong programming skills in C/C++ and Python, as well as foundational knowledge of machine learning algorithms. Experience with embedded systems development tools (such as ARM Cortex, Raspberry Pi, or Arduino), version control systems, and familiarity with ML frameworks like TensorFlow Lite or Edge Impulse is often required. Analytical thinking, problem-solving ability, and effective teamwork are vital soft skills for success in this role. These skills and qualities are crucial for efficiently developing, optimizing, and deploying machine learning solutions on resource-constrained embedded platforms.

What are some typical projects or tasks I might work on during an Embedded Machine Learning Internship?

During an Embedded Machine Learning Internship, you can expect to work on projects such as optimizing machine learning models to run efficiently on hardware with limited resources, integrating AI algorithms into embedded systems (like microcontrollers or IoT devices), and performing real-time data processing. You'll likely collaborate closely with software engineers and hardware designers to test models on physical devices, debug performance issues, and contribute to documentation. These experiences provide practical exposure to the challenges of deploying AI in real-world, resource-constrained environments and help build skills valuable for a future career in embedded AI.

What is an Embedded Machine Learning Internship?

An Embedded Machine Learning Internship is a temporary position designed for students or recent graduates to gain hands-on experience in developing and deploying machine learning algorithms on embedded systems. These internships typically involve working with hardware such as microcontrollers, sensors, or edge devices, and using specialized tools to optimize machine learning models for low-power and resource-constrained environments. Interns collaborate with engineers and data scientists to create efficient, real-world AI solutions that run directly on devices rather than relying on cloud computing. This role helps bridge the gap between theoretical machine learning concepts and practical implementation on embedded platforms.
What are the most commonly searched types of Embedded Machine Learning jobs in Massachusetts? The most popular types of Embedded Machine Learning jobs in Massachusetts are:
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What cities in Massachusetts are hiring for Embedded Machine Learning Internship jobs? Cities in Massachusetts with the most Embedded Machine Learning Internship job openings:
Embedded Machine Learning Internship jobs near you
Infographic showing various Embedded Machine Learning Internship job openings in Massachusetts as of May 2026, with employment types broken down into 41% Full Time, 52% Part Time, 2% Temporary, and 5% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

MORSE Corp

Cambridge, MA • On-site

Other

Posted 25 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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