Senior Machine Learning Engineer – AI/ML Compiler
$151,200 - $226,800 USD yearly
Originally posted 9 September 2026 by the employer — open 1 day.
About the role
You will build and maintain machine learning compiler technologies that convert AI models from PyTorch or ONNX into efficient code for CPU, GPU, and NPU processors.
What you'll do
- Build and maintain machine learning compiler technologies to generate efficient code for device chips (CPU, GPU, NPU).
- Contribute to the AI hub compiler, ONNX Runtime QNN, performing graph optimization, partitioning, and ensuring models function correctly across backends.
- Develop debugging tools to identify and resolve failures, accuracy loss, or slowdowns, providing clear diagnostics.
- Solve open-ended problems independently, mentor teammates, and provide technical guidance.
- Clearly explain complex compiler concepts to chip engineers, business partners, and outside developers.
What you'll need
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field and 2+ years of relevant work experience; OR Master's degree in a related field and 1+ year of relevant work experience; OR PhD in a related field.
- Proficiency in Python and C.
- Solid understanding of ML compiler concepts (graph IRs, operator fusion, shape inference, lowering passes, backend partitioning).
- 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 (LiteRT, ExecuTorch, or ONNXRuntime).
Nice to have
- 3 years of industry experience in ML infrastructure, compiler engineering, or AI framework development.
- Familiarity with SoC-level constraints (memory bandwidth, compute precision, NPU/DSP execution) and hardware-specific runtimes (QAIRT/QNN).
- Experience building automated CI/CD pipelines for model compilation and validation at scale.
- Proficiency with git and software engineering best practices.
Skills: ML compiler, MLIR, ONNX, TVM, PyTorch, NPU
This role has been open 0 days — well below the 63-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
508
|
Median days open
63 d
|
Median salary
$224k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Qualcomm | All employers we track in this specialty (508 roles · 79 employers) |
|---|---|---|
| Open roles in this specialty | 107 | 508 |
| Open roles in the wider Software, Firmware & Systems family | 713 | 5650 · 142 employers |
| Median days open | 98 d | 63 d (+35 d vs this employer) |
| Median salary (USD postings) | — | $224k |
Skills observed across this category: ML compiler, MLIR, ONNX, TVM, PyTorch, NPU
Who's hiring in this category
- Qualcomm (this employer) · 107 open roles · median 98 d
- NVIDIA · 88 open roles · median 60 d
- AMD · 44 open roles · median 63 d
- Micron Technology · 27 open roles · median 47 d
- Mobileye · 21 open roles · median 44 d
- NXP Semiconductors · 11 open roles · median 64 d
How we counted: 508 open AI/ML Hardware Engineering (AI ML Hardware) roles from 79 employers tracked in the SemiconductorJobs index, counted 10 Sept 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.