Sr. Staff Engineer, Machine Learning Engineering (Quantization SW)

1 Day ago • 4 Years + • $178,400 PA - $267,600 PA

Research Development

Job Description

Qualcomm AI Research is seeking a Sr. Staff Engineer for Machine Learning Engineering, focusing on Quantization SW. This role involves advancing Gen AI Technology for the Edge, including model fine-tuning, hardware acceleration, and quantization. The successful candidate will work in a dynamic research environment, designing, developing, and testing model optimization techniques like graph optimization, pruning, and quantization, contributing to the deployment of intelligent solutions on various devices.

Good To Have:

Strong Software Engineering/Development skills combined with a solid foundation in AI and general ML techniques.
Proven hands-on experience evaluating and optimizing Generative AI workflows for accuracy, performance, and other key metrics.
Prior experience with ML model optimization frameworks and a familiarity with applying techniques such as quantization, pruning etc.
Knowledge of neural networks, with hands-on experience using ML frameworks such as PyTorch, ONNX etc.
Strong Python design and implementation skills.
Strong general analytical and debugging skills.
Prior experience working in agile environments.
Prior experience in collaborating with multi-disciplinary teams across time zones.
Strong leadership skills as a mentor, team player, communicator and presenter.
Experience deploying GenAI LLM/LVM models on edge devices.
Prior experience with model quantization, profiling and running models on edge devices.
Prior experience with frameworks like Huggingface Optimum, ONNX runtime and OpenVino.
Proven hands-on experience establishing a high-quality software delivery process using industry best-practices (code review, CI/CD, automation, etc.) is a plus.

Must Have:

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 6+ 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 5+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR PhD in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Work in a dynamic research environment.
Be part of a multi-disciplinary team of researchers and software engineers who work with cutting edge AI frameworks and tools.
Architect, design, develop and test model optimization techniques that include graph optimization, pruning and quantization.

Perks:

Qualcomm offers a world-class health benefit option providing world-class coverage to employees and their eligible dependents.
Our programs are designed to help employees build and prepare for a financially secure future.
Our self and family resources help you build emotional/mental strength and resilience, as well as define your purpose — in life and at work.
Qualcomm’s wellbeing programs and resources offer support to help employees Live+Well and Work+Well, so they can unlock their full potential at home, at work, and everywhere between.
Access to continuous learning and development programs.
Tuition reimbursement.
Mentorships.

Add these skills to join the top 1% applicants for this job

team-management

problem-solving

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game-texts

quality-control

agile-development

pytorch

ci-cd

neural-networks

python

machine-learning

Job Posting Date

2025-10-24

General Summary:

Artificial Intelligence is changing the world for the benefit of human beings and societies. QUALCOMM, as the world's leading mobile computing platform provider, is committed to enable the wide deployment of intelligent solutions on all possible devices – like smart phones, autonomous vehicles, robotics and IOT devices. Qualcomm is creating the building blocks for the intelligent edge.

We are part of Qualcomm AI Research, and we focus on advancing Gen AI Technology for the Edge – including model fine tuning, hardware acceleration, model quantization, edge inference and related fields. Come join us on this exciting journey.

The successful applicant should have a strong theoretical background and proven hands-on experience with enabling on-device AI using modern software engineering best practices.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

• Master's degree in Computer Science, Engineering, Information Systems, or related field and 5+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

• PhD in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Responsibilities:

Work in a dynamic research environment,
Be part of a multi-disciplinary team of researchers and software engineers who work with cutting edge AI frameworks and tools.
Architect, design, develop and test model optimization techniques that include - but are not limited to - graph optimization, pruning and quantization.

Preferred Skills and Experience:

Strong Software Engineering/Development skills combined with a solid foundation in AI and general ML techniques.
Proven hands-on experience evaluating and optimizing Generative AI workflows for accuracy, performance, and other key metrics.
Prior experience with ML model optimization frameworks and a familiarity with applying techniques such as quantization, pruning etc.
Knowledge of neural networks, with hands-on experience using ML frameworks such as PyTorch, ONNX etc.
Strong Python design and implementation skills.
Strong general analytical and debugging skills.
Prior experience working in agile environments.
Prior experience in collaborating with multi-disciplinary teams across time zones.
Strong leadership skills as a mentor, team player, communicator and presenter.
Experience deploying GenAI LLM/LVM models on edge devices.
Prior experience with model quantization, profiling and running models on edge devices.
Prior experience with frameworks like Huggingface Optimum, ONNX runtime and OpenVino.
Proven hands-on experience establishing a high-quality software delivery process using industry best-practices (code review, CI/CD, automation, etc.) is a plus.

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).

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Pay range and Other Compensation & Benefits:

$178,400.00 - $267,600.00

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.