Qualcomm Technologies, Inc.
Engineering Group, Engineering Group > Machine Learning Engineering
General Summary:
About the Role
Join the Qualcomm AI Hub team and help developers integrate machine learning into their products and experiences: https://aihub.qualcomm.com/
Inthisroleyou willdevelop tools tohelp developersoptimizeand deploy machine learning models on edge and mobile hardware. AIMETis Qualcomm'sopen-source library forstate-of-the-artmodel quantization, and compression techniques. You will develop and supportcutting-edgemodel optimization workflows — pushing the boundary ofwhat'spossible on resource-constrained hardware. Applications range from quantizing large language models (LLMs) and generative AI models to compressing latency-critical vision, audio, and multimodal networks for deployment on Qualcomm Snapdragon and other edge SoCs.
For this role we areseekinga talented and motivated Staff Software Engineer withexpertiseintheoptimizingand deployingML models– especially for edge devices
What You'll Do
Design, develop, andmaintainquantization algorithms and compression pipelines within the AIMET framework (PTQ, QAT, mixed-precision,AdaScaleetc.)
Implement advanced quantization techniques including weight-only quantization, activation quantization, KV-cache quantization, and sub-4-bit quantization for LLMs and generative AI models
Build tooling to analyze, profile, and debug model accuracy degradation caused by quantization
Integrate AIMET workflows with popular ML frameworks —PyTorchand ONNX
Develop APIs and developer-facing tooling to make AIMET accessible and easy to use for external customers and design partners
Integrate AIMET in AI Hub Workbench Quantize job to enable Quantization at large scale.
Own end-to-end quantization and optimization of models published on Qualcomm AI Hub, ensuring they meet accuracy, latency, and power targets on Qualcomm hardware
Quantize andvalidatea broad range of model families — vision transformers, LLMs, diffusion models, speech, and multimodal architectures — for deployment via AI Hub
Develop andmaintainautomated quantization pipelines and evaluation harnesses to scale model onboarding across AI Hub's growing model catalog
Minimum Qualifications:
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ 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 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Preferred Qualifications:
3+ years of industry experience in machine learning, deep learning, or AI infrastructure
Strongproficiencyin Python, with hands-on experience inPyTorch, ONNX and/or TensorFlow
Solid understanding of neural network architectures — CNNs, Transformers, LLMs, diffusion models, multimodal models
Experience with model quantization techniques — PTQ, QAT, weight-only quantization, mixed-precision, sub-4-bit methods
Hands-on experience quantizing LLMs (GPT,LLaMA, Mistral, Falcon, or similar families) for inference optimization
Familiarity with AIMET, GPTQ, AWQ,SmoothQuant, or similar quantization frameworks is a strong plus
Experience working with ONNX,TFLiteLiteRT, or other model interchange formats
Understanding of hardware constraints: memory bandwidth, compute precision (INT4/INT8/FP16/BF16), and NPU/DSP execution
Experience collaborating across teams or BUs to drive technical alignment and model delivery
Proficiencywith git and software development best practices
Strong written and verbal communication skills — ability to write clean APIs, documentation, and engage directly with external developers
Experience with C++ for performance-critical components is a bonus
Familiarity with ARM processors and mobile SoC architecture (Snapdragon) is a plus
Experience with automated evaluation pipelines and model benchmarking at scale is a plus
Level of Responsibility
Works independently with minimal supervision
Provides technical guidance and mentorship to other team members
Decision-making is significant and affects work beyond the immediate team
Requiresstrong communicationskills to convey complex quantization concepts to varied audiences — from hardware engineers and BU partners to external researchers and application developers
Has meaningful influence on the AIMET product roadmap, AI Hub model catalog, and cross-BU quantization strategy
Tasks are open-ended; planning, prioritization, and problem-solving are core to the role
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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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.
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Pay range and Other Compensation & Benefits
$158,400.00 - $237,600.00
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
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