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Hourly Embedded Machine Learning Jobs in Boston, MA

Machine Learning Engineer - Edge

Lowell, MA ยท 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 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 Embedded Software Engineer

Boston, MA ยท On-site +1

$134K - $176K/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 ...

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 Perception Researcher

Cambridge, MA ยท On-site +1

$82K - $220K/yr

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 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 ...

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 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 ...

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Showing results 1-20

Hourly Embedded Machine Learning information

See Boston, MA salary details

$76K

$166.6K

$189K

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

As of Jul 1, 2026, the average yearly pay for hourly embedded machine learning in Boston, MA is $166,636.00, according to ZipRecruiter salary data. Most workers in this role earn between $142,900.00 and $187,900.00 per year, depending on experience, location, and employer.

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 Boston, MA? The most popular types of Embedded Machine Learning jobs in Boston, MA are:
What job categories do people searching Hourly Embedded Machine Learning jobs in Boston, MA look for? The top searched job categories for Hourly Embedded Machine Learning jobs in Boston, MA are:
What cities near Boston, MA are hiring for Hourly Embedded Machine Learning jobs? Cities near Boston, MA with the most Hourly Embedded Machine Learning job openings:

Machine Learning Engineer - Edge

GN Group

Lowell, MA โ€ข On-site, Remote

$86K - $135K/yr

Full-time

Medical, Retirement, PTO

Posted 3 days ago


Job description

Machine Learning Engineer - Edge

*Please consider before applying: This is a hybrid role, and candidates must reside within a commutable distance of one of our offices in either Dover, NH, or Lowell, MA.

Turn up the volume on your career as Cloud AI/ML Engineer

GN brings people closer through our advanced intelligent hearing, audio, video, and gaming solutions. Inspired by people and driven by innovation, we deliver technology that enhances the senses of hearing and sight.

We help people with hearing loss overcome real-life challenges, improve communication and collaboration for businesses, and provide great experiences for audio and gaming enthusiasts.

The team you will be part of

You will be joining our team focused on developing the Jabra Perform and BlueParrott product lines to advance solutions for frontline workers.

As part of the team, you will design and deploy on device machine learning models that power speech enhancement, augmented hearing, and real-time environmental awareness. You will train, finetune, and compress models to run efficiently on resource-constrained edge hardware without compromising accuracy or performance.

You will bridge the gap between software and hardware; collaborating closely with hardware engineers to ensure AI models are well integrated into the device architecture. Your work will also include optimizing algorithms for low power environments and maintaining the software libraries, tools, and frameworks that enable modern edge AI development.

Your contribution is appreciated, and you will

  • Develop and optimize AI/ML models specifically designed for resourceconstrained edge devices.
  • Collect, preprocess, and analyze large and complex datasets to train, finetune, and validate models.
  • Apply techniques such as model compression, quantization, pruning, and distillation to improve efficiency and runtime performance.
  • Ensure models perform reliably in realworld environments, meeting both functional and nonfunctional requirements.
  • Collaborate closely with hardware engineers and other crossfunctional teams to align AI/ML solutions with device architecture and system constraints.
  • Develop effective working relationships with technical experts, stakeholders, and leaders across the organization.
  • Identify, communicate, and manage technical risks throughout the project lifecycle.

Sounds good so far? To perform well in this role, we expect you to have

  • 2+ years of experience developing machine learning solutions, including work in audio and speech processing.
  • Proficient in programming with C, C++, and Python.
  • Experience with machine learning frameworks such as TensorFlow Lite, PyTorch, or comparable edge-focused toolchains.
  • Solid theoretical and practical understanding of ML architecture design, training, evaluation, and deployment workflows.
  • Understanding of model compression, quantization, and other optimization techniques for resource constrained edge devices.
  • Experience with embedded systems and hardware platforms.
  • Fundamentals of audio and speech signal processing.

Pay Transparency Notice

  • Depending on your work location, the target annual salary for this position can range from $86,000.00 to $135,000.00. In addition, you may be eligible for a discretionary bonus.
  • Compensation for roles at GN depends on a wide array of factors including but not limited to location, role, skill set, and level of experience.
  • To remain competitive, GN offers a competitive benefits package, including annual bonuses, health insurance, a 401(k) plan, paid time off and paid holidays.

We encourage you to apply

Even if you do not match all the above-mentioned skills, we will gladly receive your application if you think you have transferable skills. We greatly appreciate a mindset and motivation that aligns with our core values, helping both you and your team to thrive within the GN organization.

We are focused on an inclusive recruitment process

All applicants will receive equal consideration for employment.

Disability Accommodation

If you have a disability and you believe you need a reasonable accommodation in order to search for a job opening or to submit an online application, please e-mail careers.us@gn.com. This email is provided for the purpose of supporting applicants who have a disability that prevents them from being able to apply online. Only emails received for this purpose will be returned. Emails left for other purposes, such as following up on an application or technical issues not related to a disability, will not receive a response.

Join us in bringing people closer

GN brings people closer through our advanced intelligent hearing, audio, video, and gaming solutions. Inspired by people and motivated by innovation, we deliver technology that enhances the senses of hearing and sight. We enable people with hearing loss overcome real-life problems, improve communication and collaboration for businesses, and provide great experiences for audio and gaming users.

GN Store Nord A/S has entered into a definitive agreement for the sale of GN's Hearing business to Amplifon S.p.A. to create a global leader in audiology. For GN Group, this creates an opportunity to expand our position in the large audio and video peripherals markets. Read more about the announcement here.

We hope you will join us on this journey and look forward to receiving your application.

#LI-GNGroup