Staff Machine Learning Engineer – AI/ML Compiler

Qualcomm; San Diego (CA); On-site; USD 160,500 - 240,700; Full time

Benefits offered by this job

Annual discretionary bonus program

Opportunity for RSU grants

Comprehensive benefits package

Job summary

A leading technology company is seeking an experienced Machine Learning Engineer to own the infrastructure for model compilations within the Qualcomm AI Hub. You will design and maintain the end-to-end compilation pipeline, ensuring efficient model execution across various backends. Candidates should have a relevant degree and substantial experience in compiler engineering, ML infrastructure, and proficiency in Python and C++. A competitive salary range of $160,500 to $240,700 is offered, alongside a comprehensive benefits package.

Qualifications

• Bachelor's, Master's, or PhD in relevant field with appropriate work experience.
• 3+ years of industry experience in ML infrastructure or compiler engineering.
• Proficiency in Python and C++.

Responsibilities

• Design, develop, and maintain the compilation pipeline for Qualcomm AI Hub Workbench.
• Build automated compilation pipelines and CI/CD evaluation harnesses.
• Collaborate with internal teams for model onboarding.

Skills

Compiler engineering

Python

C++

Machine Learning infrastructure

Graph IRs

Automation

Technical documentation

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field

Master's degree in Computer Science, Engineering, Information Systems or related field

PhD in Computer Science, Engineering, Information Systems, or related field

Tools

PyTorch

ONNX

CI/CD pipelines

Job description

Overview

Company
Qualcomm Technologies, Inc.

Job Area

Job Area
Engineering Group, Engineering Group > Machine Learning Engineering

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.

Responsibilities

• 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

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Pay Range And Other Compensation & Benefits

$160,500.00 - $240,700.00

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. 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. In addition, our benefits package supports your success at work, at home, and at play. Your recruiter can discuss details, and you can review more about our US benefits at the linked page.

If you would like more information about this role, please contact Qualcomm Careers.