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Embedded Machine Learning Internship Jobs in Boston, MA

Senior Machine Learning Scientist

Boston, MA

$99.40K - $135.80K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI ... IoT devices, or embedded systems is highly desirable. * Excellent problem-solving skills ...

Draper's Perception and Embedded Machine Learning Group seeks an engineer to help develop, integrate, and deploy advanced perception systems, including for autonomous vehicles and robots able to ...

Draper's Perception and Embedded Machine Learning Group seeks an engineer to help develop, integrate, and deploy advanced perception systems, including for autonomous vehicles and robots able to ...

Draper's Perception and Embedded Machine Learning Group seeks an engineer to help develop, integrate, and deploy advanced perception systems, including for autonomous vehicles and robots able to ...

Senior Machine Learning Scientist

Boston, MA · On-site

$99.40K - $135.80K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI ... IoT devices, or embedded systems is highly desirable. * Excellent problem-solving skills ...

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Embedded Machine Learning Internship information

See Boston, MA salary details

$27.7K

$46.3K

$95.6K

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

As of May 31, 2026, the average yearly pay for embedded machine learning internship in Boston, MA is $46,263.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,300.00 and $50,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Embedded Machine Learning 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 Boston, MA? The most popular types of Embedded Machine Learning jobs in Boston, MA are:
What job categories do people searching Embedded Machine Learning Internship jobs in Boston, MA look for? The top searched job categories for Embedded Machine Learning Internship jobs in Boston, MA are:
Senior Machine Learning Scientist

Senior Machine Learning Scientist

Axon

Boston, MA

$99.40K - $135.80K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 20 days ago


Axon rating

8.6

Company rating: 8.6 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

15th of 137 rated electronics manufacturers


Job description

Your Impact
We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a key member of our research and development efforts, you will play a crucial role in advancing the state-of-the-art in Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Computer Vision and GenAI technologies for law enforcement and beyond. You will collaborate with cross-functional teams to design, develop, and deploy cutting-edge LLM, MLLM, CV models and algorithms and solutions that enable intelligent reasoning, perception and understanding of multimodal data.
What You'll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

  • US: Seattle, Boston, Scottsdale
Responsibilities
  • Own one or more key technical areas across LLM, MLLM, CV product portfolio.
  • Provide technical leadership to junior scientists, guiding the transition of R&D concepts into impactful Axon product feature.
  • Research and develop cutting-edge techniques in LLM, MLLMs, GenAI, and Computer Vision across cloud, devices and sensors based data sources.
  • Design and implement efficient and scalable MLLM models for inference and analysis of multimodal data.
  • Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition, Object Tracking, Segmentation, and Scene Understanding.
  • Optimize AI models, algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
  • Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and optimize algorithms for specific hardware architectures.
  • Evaluate the performance of LLM, MLLM, CV models using real-world datasets and design experiments to validate their effectiveness.
  • Stay up-to-date with the latest research trends and advancements in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant findings into our projects.
  • Contribute to patent disclosures, academic publications, and technical documentation to share insights and findings with the broader community.
  • Experience coach and mentor junior scientists.
What You Bring
  • PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML Scientist experience in Computer Science or a related field with a focus on LLM, MLLMs, Computer Vision, GenAI.
  • Proven track record of research excellence in LLM, MLLM, Computer Vision, Robotics Perception, GenAI, demonstrated through publications in top-tier conferences or journals.
  • Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system.
  • Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches and architectures, train/evaluate/tune models and implement the end-to-end training pipeline.
  • Leverage state-of-the-art research to deliver high quality models enabling multiple AI projects at scale.
  • Contribute back to the research community via academic publications, tech blogs, open-source code and contributing to internal/external AI challenges
  • Experience in developing computer vision algorithms for resource-constrained devices such as mobile phones, IoT devices, or embedded systems is highly desirable.
  • Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
  • Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.
Benefits that Benefit You
  • Competitive salary and 401k with employer match
  • Discretionary paid time off
  • Paid parental leave for all
  • Medical, Dental, Vision plans
  • Fitness Programs
  • Emotional & Mental Wellness support
  • Learning & Development programs
  • And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Boston, MA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.


What Axon employees say

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