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Remote Machine Learning Ops Engineer Jobs in Massachusetts

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 candidates must reside within a commutable distance of one of our offices in either Dover, NH, or Lowell ...

The Core for Computational Biomedicine (CCB) in the Department of Biomedical Informatics (DBMI) at Harvard Medical School (HMS) is looking for a Machine Learning Engineer with advanced expertise to ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

ASUS Robotics & AI Center Senior Machine Learning Engineer The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global research and development team. This role ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$149K - $245K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$140K - $190K/yr

By joining our team as a Senior Machine Learning Engineer , you will play a pivotal role in building cutting-edge AI products that directly impact how new therapies reach patients. We're looking for ...

Machine Learning Team Lead

Somerville, MA · On-site +1

$170K - $210K/yr

Lead and support Modulate's machine learning research and engineering team * Ensure the team is ... Hybrid work with core in-office days and flexible remote options * Leadership and technical ...

Machine Learning Team Lead

Somerville, MA · On-site +1

$170K - $210K/yr

Collaborate with engineers, researchers, and executives (CTO, CEO, VP Product/Design) on ML ... Hybrid work with core in-office days and flexible remote options > * Leadership and technical ...

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Remote Machine Learning Ops Engineer information

What job categories do people searching Remote Machine Learning Ops Engineer jobs in Massachusetts look for? The top searched job categories for Remote Machine Learning Ops Engineer jobs in Massachusetts are:
What cities in Massachusetts are hiring for Remote Machine Learning Ops Engineer jobs? Cities in Massachusetts with the most Remote Machine Learning Ops Engineer job openings:
Infographic showing various Remote Machine Learning Ops Engineer job openings in Massachusetts as of May 2026, with employment types broken down into 66% Full Time, 32% Part Time, 1% Contract, and 1% Nights. Highlights an 36% Physical, 18% Hybrid, and 46% Remote job distribution.

Machine Learning Engineer - Edge

GN Group

Lowell, MA • On-site, Remote

$86K - $135K/yr

Full-time

Medical, Retirement, PTO

Posted 29 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