1

Hourly Embedded Machine Learning Jobs in Massachusetts

Staff Embedded ML Engineer, Edge AI

Boston, MA

$142K - $187K/yr

  • Medical

  • Retirement

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

  • Medical

  • Retirement

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

Natick, MA ยท On-site

$115K - $225K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The team works across custom hardware, optimized embedded systems, and next-generation algorithm ... Research, design, and implement efficient deep learning models for industrial machine vision tasks ...

Senior Machine Learning Engineer

Natick, MA ยท On-site

$115K - $225K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Senior Machine Learning Engineer

Boston, MA ยท On-site +1

$161K - $246K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Staff Machine Learning Engineer

Waltham, MA ยท On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... 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 ...

Staff Machine Learning Engineer

Waltham, MA ยท On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... 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

$99K - $135K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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

Hourly Embedded Machine Learning information

What are the key skills and qualifications needed to thrive as an hourly embedded machine learning engineer, and why are they important?

To thrive as an Hourly Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

How does an hourly embedded machine learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What is an hourly embedded machine learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

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

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

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

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

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

Whoi

Falmouth, MA โ€ข On-site

$113K - $148K/yr

Full-time

Posted 10 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.