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Deep Learning Quantization Jobs in Raleigh, NC (NOW HIRING)

Qualcomm

Sr Software Engineer, AI Tools - Quantizer

Raleigh, NC · On-site

$119.10K - $157K/yr

... Deep Learning frameworks like PyTorch, Tensorflow, ONNX, JAX Preferred Qualifications * 2+ years Python programming experience * Experience / exposure to Quantization techniques - PTQ, QAT, AWQ ...

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Deep Learning Quantization information

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$10.7K

$81.5K

$136.1K

How much do deep learning quantization jobs pay per year?

As of May 28, 2026, the average yearly pay for deep learning quantization in Raleigh, NC is $81,544.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,000.00 and $135,100.00 per year, depending on experience, location, and employer.

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

To excel as a Deep Learning Quantization Engineer, you need a strong background in machine learning, applied mathematics, and computer science, usually supported by an advanced degree in a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), quantization toolkits, and hardware acceleration platforms is crucial. Analytical thinking, problem-solving, and clear technical communication are standout soft skills in this role. These abilities are essential for efficiently optimizing models for deployment on resource-constrained hardware while maintaining accuracy and performance.

What are some common challenges faced when implementing deep learning quantization in production environments?

One of the main challenges in implementing deep learning quantization is balancing model accuracy with computational efficiency, as quantization can sometimes lead to a drop in model performance. Additionally, ensuring hardware compatibility and optimizing for different devices (such as CPUs, GPUs, or edge devices) can require extensive testing and tuning. Collaboration with data scientists, software engineers, and hardware specialists is often essential to successfully deploy quantized models at scale. Staying updated with the latest quantization techniques and frameworks is also important for overcoming these challenges.

What is deep learning quantization?

Deep learning quantization is the process of reducing the precision of the numbers used to represent a neural network's parameters, activations, or both. By converting the typically used 32-bit floating-point values to lower bit-width formats such as 16-bit or 8-bit integers, quantization significantly reduces the memory footprint and computational requirements of deep learning models. This technique helps deploy models efficiently on edge devices and mobile hardware while maintaining acceptable accuracy levels. Quantization is widely used in model optimization for faster inference and lower power consumption.

What is the difference between Deep Learning Quantization vs Machine Learning Engineer?

AspectDeep Learning QuantizationMachine Learning Engineer
Required CredentialsAdvanced degrees in AI, Computer Science, or related fields; knowledge of neural networksBachelor's or Master's in CS, Data Science, or related fields; programming skills
Work EnvironmentResearch labs, AI development teams, hardware optimization settingsSoftware development teams, data-driven projects, product-focused environments
Industry UsageAI hardware optimization, model deployment, edge computingModel development, data analysis, software solutions across industries

Deep Learning Quantization focuses on reducing model size and improving inference speed through techniques like weight and activation quantization, often in hardware or embedded systems. Machine Learning Engineers develop, implement, and optimize machine learning models for various applications. While both roles require knowledge of AI and programming, Deep Learning Quantization is more specialized in model optimization techniques, whereas Machine Learning Engineers work broadly on model development and deployment.

What are popular job titles related to Deep Learning Quantization jobs in Raleigh, NC? For Deep Learning Quantization jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Deep Learning Quantization jobs in Raleigh, NC look for? The top searched job categories for Deep Learning Quantization jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Deep Learning Quantization jobs? Cities near Raleigh, NC with the most Deep Learning Quantization job openings:
Deep Learning Quantization jobs near you
Sr Software Engineer, AI Tools - Quantizer

Sr Software Engineer, AI Tools - Quantizer

Qualcomm

Raleigh, NC • On-site

$119.10K - $157K/yr

Full-time

Posted 7 days ago

Job description

Company:
Qualcomm Technologies, Inc.
Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering
General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drive digital transformation, creating a smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will develop and implement cutting-edge machine learning techniques that enable the efficient utilization of state-of-the-art solutions across various technology verticals.
In this position you will be responsible for the software design and development of quantization tooling within the AISW Tools team. Our inference engine empowers developers to deploy neural network models on Snapdragon platforms at exceptional speeds while maintaining minimal power consumption. You will participate in the agentic transformation of Qualcomm's development and tooling workflow. You will have the opportunity to show your passion for software design and development with your analytical, design, programming, and debugging skills.
All Qualcomm employees are expected to actively support diversity on their teams, and in the Company.
Minimum Qualifications:
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field.
Responsibilities
  • Collaborate with cross-functional teams in the AI Software team at Qualcomm to gain knowledge of the capabilities of QAIRT SDK and use it to optimize inference of AI models on Qualcomm AI accelerator IP.
  • Validate and optimize the performance and accuracy of quantized models through detailed analysis and testing of machine learning use cases.
  • Debug complex issues, perform root cause analysis, and ensure high system reliability.
  • Contribute to the team's adoption of agentic AI workflows - leveraging tools such as Claude Code, or similar frameworks - to automate quantization experimentation, hyperparameter search, and model evaluation pipelines.
  • Participate in design and code reviews.
  • Work independently and lead junior team members. Your decision-making will impact your direct area of work and the work group.

Minimum Qualifications
  • Bachelor's degree or equivalent in Engineering, Information Systems, Computer Science, or related field
  • 4+ years software development experience using Python and/or C/C++
  • Strong software development skills (e.g. data structure and algorithm design, object oriented or other software design paradigm knowledge, software debugging and testing, etc.)
  • Strong communication skills (verbal, presentation, written)
  • Solid understanding of Machine Learning and Deep Learning theory
  • Experience working with one of the Deep Learning frameworks like PyTorch, Tensorflow, ONNX, JAX

Preferred Qualifications
  • 2+ years Python programming experience
  • Experience / exposure to Quantization techniques - PTQ, QAT, AWQ, SpinQuant, etc.
  • Familiarity with different NN architectures: DNNs, CNNs, RNNs/LSTMs, GANs, LLMs, etc.
  • Experience with AIMET, TorchAO or other quantization-focused libraries in the PyTorch ecosystem
  • Familiarity with GenAI model architectures and challenges working with them - LLM, LVM, LMM
  • Experience with optimizing software, specifically AI graph workloads, for embedded platforms
  • Familiarity with agentic AI frameworks (e.g. Claude Code) and experience applying them to automate experimentation or evaluation workflows
  • Ability to collaborate across a globally diverse team and multiple interests

Education Requirements
  • Required: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.
  • Preferred: Master's in Computer Science or Computer Engineering

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
Pay range and Other Compensation & Benefits:
$126,700.00 - $190,100.00
The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer - and you can review more details about our US benefits at this link.
If you would like more information about this role, please contact Qualcomm Careers.
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About Qualcomm

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Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including 5G-enabled smartphones that double as pro-level cameras and gaming devices, smarter vehicles and cities, and the technology behind the smart, connected factories that manufactured your latest purchase. Our powerful connectivity solutions keep you connected—even in remote areas. Qualcomm 5G and AI innovations are the power behind the connected intelligent edge. You’ll find our technologies behind and inside the innovations that deliver significant value across multiple industries and to billions of people every day.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1985

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