Back to jobs

Staff Machine Learning Engineer – AI/ML Compiler

Santa Clara, CA, US; San Diego, CA, US

Pay
$174,000–261,000/yearAnnual period assumed · Location-specific pay — pay source
Pay range and Other Compensation & Benefits: $174,000.00 - $261,000.00 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.
Read the full posting
Work setup
Unconfirmed
Employment
Unconfirmed
Apply at Qualcomm

What you’ll work on

Full posting

Qualcomm AI Hub is the platform for on-device AI — enabling developers to easily integrate, optimize, and deploy ML models on Qualcomm devices.

Join the Qualcomm AI Hub Compiler team and own the infrastructure that powers these model compilations.

What you’ll bring

All qualifications

Core experience

  • 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.
Qualification wording
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.

Tools in this posting

  • Python
  • PyTorch
  • C++
Source — Tool mentions in context
* 3+ years of industry experience in ML infrastructure, compiler engineering, or AI framework development * Proficient in Python and C++ * Solid understanding of ML compiler concepts (graph IRs, operator fusion, shape inference, lowering passes, backend partitioning) and hands-on experience with one or more compiler stacks such as MLIR, ONNX, or TVM
About the Role Qualcomm AI Hub is the platform for on-device AI — enabling developers to easily integrate, optimize, and deploy ML models on Qualcomm devices. Qualcomm AI Hub Workbench lets developers compile trained PyTorch or ONNX models into deployable artifacts targeting a variety of runtimes — LiteRT, ONNXRuntime, or Qualcomm AI Engine Direct SDK (QAIRT) — and profile and validate them on real Qualcomm devices hosted in the cloud. Join the Qualcomm AI Hub Compiler team and own the infrastructure that powers these model compilations. You will work across the full compilation pipeline — from model ingestion and graph optimization to backend dispatch across CPU, GPU, and NPU — ensuring models compile correctly, execute efficiently, and scale across a growing catalog of on-device use cases spanning vision, audio, speech, and multi-modal models.
Compiler Pipeline & Infrastructure * Design, develop, and maintain the end-to-end compilation pipeline powering Qualcomm AI Hub Workbench, from PyTorch and ONNX model ingestion through graph optimization to deployable artifacts targeting LiteRT, ONNXRuntime, or QAIRT on Snapdragon SoCs * Build and maintain ONNX-based compilation paths using ONNX IR: graph transformation passes, op validation, and opset compatibility handling
* Build and maintain ONNX-based compilation paths using ONNX IR: graph transformation passes, op validation, and opset compatibility handling * Build and maintain PyTorch compilation paths consuming torch.export output, including dynamic shapes, custom ops, and ATen IR decomposition * Contribute to ONNXRuntime QNN execution provider: graph optimizations, graph partitioning, and op validation and lowerings
* Solid understanding of ML compiler concepts (graph IRs, operator fusion, shape inference, lowering passes, backend partitioning) and hands-on experience with one or more compiler stacks such as MLIR, ONNX, or TVM * Experience with PyTorch model export (torch.export, torch.compile, FX, ATen IR) and on-device deployment frameworks such as LiteRT, ExecuTorch, or ONNXRuntime * Familiarity with SoC-level constraints (memory bandwidth, compute precision, NPU/DSP execution) and hardware-specific runtimes such as QAIRT/QNN is a plus

Job description

View original posting ↗

## Company: Qualcomm Technologies, Inc. ## Job Area: Engineering Group, Engineering Group > Machine Learning Engineering General Summary: About the Role Qualcomm AI Hub is the platform for on-device AI — enabling developers to easily integrate, optimize, and deploy ML models on Qualcomm devices. Qualcomm AI Hub Workbench lets developers compile trained PyTorch or ONNX models into deployable artifacts targeting a variety of runtimes — LiteRT, ONNXRuntime, or Qualcomm AI Engine Direct SDK (QAIRT) — and profile and validate them on real Qualcomm devices hosted in the cloud. Join the Qualcomm AI Hub Compiler team and own the infrastructure that powers these model compilations. You will work across the full compilation pipeline — from model ingestion and graph optimization to backend dispatch across CPU, GPU, and NPU — ensuring models compile correctly, execute efficiently, and scale across a growing catalog of on-device use cases spanning vision, audio, speech, and multi-modal models. What You'll Do Compiler Pipeline & Infrastructure * Design, develop, and maintain the end-to-end compilation pipeline powering Qualcomm AI Hub Workbench, from PyTorch and ONNX model ingestion through graph optimization to deployable artifacts targeting LiteRT, ONNXRuntime, or QAIRT on Snapdragon SoCs * Build and maintain ONNX-based compilation paths using ONNX IR: graph transformation passes, op validation, and opset compatibility handling * Build and maintain PyTorch compilation paths consuming torch.export output, including dynamic shapes, custom ops, and ATen IR decomposition * Contribute to ONNXRuntime QNN execution provider: graph optimizations, graph partitioning, and op validation and lowerings * Collaborate with QAIRT and QNN teams to ensure correct and efficient model execution across CPU, GPU, and NPU backends * Build tooling to analyze, profile, and debug compilation failures, accuracy regressions, and performance degradations; develop clear, actionable developer-facing diagnostics Model Catalog, Automation & Collaboration * Own compilation and validation of models published on Qualcomm AI Hub, ensuring correct conversion and verified performance across supported runtime targets * Build and maintain automated compilation pipelines and CI/CD evaluation harnesses to scale model onboarding as the Qualcomm AI Hub model catalog grows * Partner with internal Business Units to onboard models through Qualcomm AI Hub compilation workflows, translating deployment constraints (target SoC, latency budgets, memory limits) into concrete compilation strategies * Author technical documentation, tutorials, and example notebooks for the Qualcomm AI Hub developer community 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 ML infrastructure, compiler engineering, or AI framework development * Proficient in Python and C++ * Solid understanding of ML compiler concepts (graph IRs, operator fusion, shape inference, lowering passes, backend partitioning) and hands-on experience with one or more compiler stacks such as MLIR, ONNX, or TVM * Experience with PyTorch model export (torch.export, torch.compile, FX, ATen IR) and on-device deployment frameworks such as LiteRT, ExecuTorch, or ONNXRuntime * Familiarity with SoC-level constraints (memory bandwidth, compute precision, NPU/DSP execution) and hardware-specific runtimes such as QAIRT/QNN is a plus * Experience building automated CI/CD pipelines for model compilation and validation at scale * Strong written and verbal communication skills; proficiency with git and software engineering best practices Level of Responsibility * Works independently on open-ended compiler and infrastructure challenges * Provides technical guidance and mentorship to team members * Decision-making has broad impact — affecting compilation correctness, runtime performance, and the developer experience across Qualcomm AI Hub * Communicates complex compiler and runtime concepts to varied audiences: SoC engineers, BU partners, and external ML developers * Has meaningful influence on the Qualcomm AI Hub compiler roadmap, model catalog strategy, and cross-team runtime integration priorities 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: $174,000.00 - $261,000.00 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.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on careers.qualcomm.com. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
Pay range and Other Compensation & Benefits: $174,000.00 - $261,000.00 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.
Location & working pattern

Santa Clara, CA, US; San Diego, CA, US

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Active
First seen by us
Aug 15, 2026
Recorded sightings
52
Last seen by us
Oct 11, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Report an error

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.