Staff Machine Learning Engineer – AI/ML Compiler

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

Job summary

Qualcomm is seeking an experienced compiler engineer to join the Qualcomm AI Hub Compiler team in Santa Clara, CA. You will design and maintain the end-to-end compilation pipeline while ensuring models compile correctly and efficiently across multiple backends.

The ideal candidate should have strong proficiency in Python and C++, as well as experience in ML infrastructure or compiler engineering. This position offers a competitive salary range from $160,500 to $240,700, along with bonuses and RSU grants.

Qualifications

• 4+ years of experience in hardware, software, or systems engineering.
• 3+ years of industry experience in ML infrastructure, compiler engineering, or AI framework development.
• Proficient in building automated CI/CD pipelines for model compilation and validation.

Responsibilities

• Design and maintain the end-to-end compilation pipeline for Qualcomm AI Hub.
• Contribute to ONNXRuntime QNN execution provider's optimizations.
• Own compilation and validation of models published on Qualcomm AI Hub.

Skills

Python

C++

ML infrastructure

compiler engineering

AI framework development

Education

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

Master's degree in related fields

PhD in related fields

Tools

ONNX

PyTorch

MLIR

TVM

Job description

Company

Qualcomm Technologies, Inc.

Job Area

Engineering Group, Engineering Group > Machine Learning Engineering

General Summary

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, software, or systems engineering experience
• Master's degree in the same fields and 3+ years of related experience
• PhD in the same fields and 2+ years of related 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 with broad impact — affecting compilation correctness, runtime performance, and 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

Equal Opportunity Employer

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need accommodation during the application/hiring process, contact disability‑[e-mail].

Pay range and Other Compensation & Benefits

$160,500.00 – $240,700.00. The above pay scale reflects the broad, minimum to maximum, pay range for this job code at the location for which it has been posted. In addition, a competitive annual discretionary bonus program and RSU grants are available. Details of benefits can be reviewed on request.