1

Embedded Machine Learning Jobs in Massachusetts (NOW HIRING)

Staff Embedded ML Engineer, Edge AI

Boston, MA ยท On-site

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

Staff Embedded ML Engineer, Edge AI

Boston, MA ยท On-site

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

Senior Machine Learning Engineer

Boston, MA ยท 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 ...

... Xometry's embedded DFM AI + IQE integration with Teamcenter and Designcenter. You will be ... machine learning engineering, with a track record of owning and delivering complex ML systems in ...

... Xometry's embedded DFM AI + IQE integration with Teamcenter and Designcenter. You will be ... machine learning engineering, with a track record of owning and delivering complex ML systems in ...

Senior Machine Learning Scientist

Boston, MA ยท On-site

$99K - $135K/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 ...

Senior Machine Learning Scientist

Boston, MA ยท On-site

$99K - $135K/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 ...

next page

Showing results 1-20

Embedded Machine Learning information

What is an embedded machine learning?

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 embedded machine learning?

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.

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:

What are popular job titles related to Embedded Machine Learning jobs in Massachusetts?

For Embedded Machine Learning jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning jobs in Massachusetts look for?

The top searched job categories for Embedded Machine Learning jobs in Massachusetts are:

What cities in Massachusetts are hiring for Embedded Machine Learning jobs?

Cities in Massachusetts with the most Embedded Machine Learning job openings:

Infographic showing various Embedded Machine Learning job openings in Massachusetts as of August 2026, with employment types broken down into 7% Internship, and 93% Full Time. Highlights an 94% In-person, and 6% Hybrid job distribution.

Software and Computer Engineer - Robotics, Machine Learning, and Embedded Systems

Falmouth, MA โ€ข On-site

$113K - $148K/yr

Full-time

Posted 19 days ago


Job description

Job Summary

Job Description

Woods Hole Oceanographic Institution (WHOI) is seeking a highly skilled Software and Computer Engineer with expertise in robotics, machine learning, embedded systems, and Linux-based software development. The successful candidate will support the design, development, integration, testing, and deployment of advanced robotic and autonomous systems for maritime and field environments.

This role requires strong hands-on engineering skills, experience integrating software and hardware, and the ability to work in operational settings, including at-sea testing and deployment. The successful candidate must be eligible to obtain and maintain a U.S. security clearance.

Essential Duties & Responsibilities

  • Design, develop, test, and maintain software for robotic, autonomous, and intelligent systems.

  • Develop embedded software for real-time and resource-constrained platforms.

  • Build and maintain Linux-based software systems, drivers, services, and tools.

  • Integrate software with sensors, actuators, embedded controllers, robotic platforms, and mission systems.

  • Apply machine learning techniques to perception, autonomy, control, classification, navigation, and decision-support applications.

  • Develop, train, evaluate, and deploy machine learning models for robotics and maritime systems.

  • Support robotic system architecture, including autonomy stacks, middleware, communications, data pipelines, and control interfaces.

  • Perform software integration, debugging, verification, and validation in laboratory, field, and maritime environments.

  • Participate in at-sea testing, demonstrations, data collection, troubleshooting, and system deployment.

  • Collaborate with mechanical, electrical, ocean, robotics, and systems engineers.

  • Produce technical documentation, test plans, software specifications, design reviews, and operational procedures.

  • Support cybersecurity, reliability, safety, and security requirements for deployed systems.

  • Contribute to research, prototyping, and the transition of advanced technologies into operational systems.

Required Qualifications

  • Bachelor's degree in computer engineering, software engineering, electrical engineering, computer science, robotics, or a closely related technical field.

  • Ph.D. in robotics, machine learning, computer engineering, computer science, electrical engineering, autonomous systems, or a related field.

  • Significant demonstrated expertise in robotics, machine learning, embedded systems, or autonomous systems.

  • Strong proficiency in software development using languages such as C, C++, Python, or Rust.

  • Experience developing embedded software for microcontrollers, single-board computers, real-time systems, or hardware-integrated platforms.

  • Experience developing, configuring, and debugging software on Linux-based systems.

  • Familiarity with robotic systems, autonomy frameworks, sensor integration, communications, and control systems.

  • Experience with machine learning frameworks, model development, data processing, and performance evaluation.

  • Ability to work in laboratory, field, and maritime environments, including at-sea testing and deployment.

  • Ability to obtain and maintain a U.S. security clearance.

  • Strong analytical, debugging, communication, and technical documentation skills.

  • Ability to work independently and as part of a multidisciplinary technical team.

Preferred Qualifications

  • Ph.D. in robotics, machine learning, computer engineering, computer science, electrical engineering, autonomous systems, or a related field.

  • Experience with maritime robotics, autonomous underwater vehicles, unmanned surface vehicles, or other fielded robotic systems.

  • Experience with ROS, ROS 2, or similar robotics middleware.

  • Experience with real-time operating systems, embedded Linux, device drivers, communication protocols, or hardware-in-the-loop testing.

  • Experience with perception, computer vision, sensor fusion, navigation, localization, mapping, autonomy, human-robot interaction, or adaptive control.

  • Experience with sonar, lidar, radar, cameras, inertial sensors, GPS/GNSS, acoustic communications, or related sensing systems.

  • Experience deploying machine learning models on embedded or edge-computing platforms.

  • Familiarity with containerization, DevOps, CI/CD, Git-based workflows, and software configuration management.

Additional Job Requirements

Salary Range:$113,650- $148,216

The salary range provided for this position reflects the expected minimum and maximum base pay for new hires. Actual level placement and compensation will be determined based on factors such as relevant skills, experience, and qualifications, as well as internal equity and market conditions. In addition to base salary, eligible employees also receive a comprehensive benefits package.

WHOI accepts applications on a rolling basis - applications will be reviewed as they are received, and we encourage you to submit your application as soon as possible to ensure full consideration. While we will continue to review applications until the position is filled, and early applicants may have an advantage in the selection process.

EEO Statement

Woods Hole Oceanographic Institution (WHOI) provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.