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Machine Learning Engineer Quantization Jobs (NOW HIRING)

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 ... Apply techniques such as model compression, quantization, pruning, and distillation to improve ...

... quantization / inference acceleration. • Work with deployment and platform teams to validate ... Engineering, Robotics, Computer Vision, Machine Learning, or a related field. • 3-5 years of ...

We're looking for researchers and experienced engineers from any background. Trading experience is ... search, machine learning systems and quantization methods, and determine what translates to ...

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

Machine Learning Engineer

Austin, TX · On-site

$140K - $180K/yr

🚀 Machine Learning Engineer 📍 Austin, TX (Hybrid/Remote Considered) 💰 $140,000 - $180,000 Base We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to ...

JOB SUMMARY Seeking a hands-on Machine Learning Engineer with strong Python programming expertise and recent PySpark experience to build, deploy, and support production-ready machine learning ...

Machine Learning Engineer Location: Arlington, VA Duration: FTE/No C2C Role: Design, develop, and maintain the product ionization of machine learning, deep learning, generative AI, large language ...

Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and ...

Machine Learning Engineer (Full time) JOB DUTIES: The Machine Learning Engineer will design, develop, deploy, and maintain advanced machine learning models and data analysis systems to support ...

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

They are seeking a Machine Learning Engineer to build systems that analyze the performance of music promotions, providing actionable insights for creators and partners. Responsibilities : • ...

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

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Showing results 1-20

Machine Learning Engineer Quantization information

See salary details

$31.5K

$128.8K

$193.5K

How much do machine learning engineer quantization jobs pay per year?

As of Jul 4, 2026, the average yearly pay for machine learning engineer quantization in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What are some common challenges Machine Learning Engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Quantization, and why are they important?

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

What does a Machine Learning Engineer Quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

What is the difference between Machine Learning Engineer Quantization vs Data Scientist?

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

More about Machine Learning Engineer Quantization jobs
What cities are hiring for Machine Learning Engineer Quantization jobs? Cities with the most Machine Learning Engineer Quantization job openings:
What states have the most Machine Learning Engineer Quantization jobs? States with the most job openings for Machine Learning Engineer Quantization jobs include:
Infographic showing various Machine Learning Engineer Quantization job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 95% Full Time, 1% Part Time, and 2% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer - Edge

GN Group

Lowell, MA • On-site, Remote

$86K - $135K/yr

Full-time

Medical, Retirement, PTO

Posted 5 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