Senior Machine Learning Engineer – AI/ML Compiler
Santa Clara, CA, US
- Pay
$151,200–226,800/yearAnnual period assumed · Location-specific pay — pay source
Pay range and Other Compensation & Benefits: $151,200.00 - $226,800.00 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 setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingBuild and maintain ML compiler technology that converts PyTorch or ONNX models to run on device CPUs, GPUs and NPUs
Do graph optimization and partitioning for AI hub compiler and ONNX Runtime QNN
Build debugging tools to find and fix failures, accuracy loss, and slowdowns
Solve open-ended problems independently while mentoring teammates
Explain complex compiler ideas to chip engineers, business partners, and outside developers
From the employer’s posting
Build & maintain machine learning compiler technologies that turn AI models (from PyTorch or ONNX) into efficient code that runs on
Contribute to AI hub compiler, ONNX Runtime QNN —doing graph optimization, partitioning, and making sure models work correctly across
Build debugging tools to spot and fix failures, accuracy loss, or slowdowns, with clear diagnostics for other developers.
Solve open-ended problems independently while mentoring teammates and giving technical guidance.
Explain complex compiler ideas clearly to chip engineers, business partners, and outside developers.
What you’ll bring
All qualificationsCore experience
- 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.
Qualification wording
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.
Education & alternatives
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. Preferred Qualifications:
Tools in this posting
- C++
- Python
- PyTorch
Source — Tool mentions in context
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 Principal Duties and Responsibilities:
Principal Duties and Responsibilities: \- Build & maintain machine learning compiler technologies that turn AI models (from PyTorch or ONNX) into efficient code that runs on device chips (CPU, GPU, and NPU processors).
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 12, 2026 · 48 days ago
- Recorded sightings
- 133
- Last seen by us
- Oct 31, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume 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.
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Job description
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Pay range and Other Compensation & Benefits: $151,200.00 - $226,800.00 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
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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