Staff Machine Learning Engineer, AI/ML Compiler

Qualcomm

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Santa Clara, CASan Diego, CA
Salary
$174,000–$261,000 / yr
Posted
40 days ago
Freshness
Confirmed live today
Closes
Mar 16, 2027

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $228k
This role $218k
$162k $290k
below market most similar roles pay here above market

This role pays less than 58% of similar roles. Most pay $200,437–$254,750 — the blue band above. At the midpoint, this role pays about $218k versus about $228k for comparable roles.

Based on 240 similar postings.

Employer

About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 575 open roles on FindRole.

Listed pay typically runs $147,900–$221,900 across 550 roles with salary data.

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At a glance

TL;DR · Staff Machine Learning Engineer, AI/ML Compiler

Staff Machine Learning Engineer – AI/ML Compiler joins the Qualcomm AI Hub Compiler team to own the infrastructure powering model compilations for on-device AI. You will design and maintain the end-to-end compilation pipeline, transforming PyTorch and ONNX models into deployable artifacts for LiteRT, ONNXRuntime, or QAIRT on Snapdragon SoCs. Daily responsibilities include building ONNX-based compilation paths, handling ATen IR decomposition, and developing graph optimization passes. You will also build automated CI/CD evaluation harnesses and tools to debug performance regressions. The role requires proficiency in Python and C++, along with expertise in ML compiler concepts like operator fusion, shape inference, and lowering passes. You will solve technical challenges regarding model ingestion, backend dispatch across CPU, GPU, and NPU, and ensuring efficient execution for vision, audio, and multi-modal models.

What does a Machine Learning Engineer earn in California?

Median $235750 from 200 postings across 34 companies.

See salary data

What you'll do

  • Design and maintain the end-to-end compilation pipeline for PyTorch and ONNX models.
  • Build ONNX-based compilation paths including graph transformation passes and opset compatibility handling.
  • Develop PyTorch compilation paths for torch.export output, dynamic shapes, and ATen IR decomposition.
  • Contribute to the ONNXRuntime QNN execution provider for graph optimizations and partitioning.
  • Build tools to analyze, profile, and debug compilation failures and performance degradations.
  • Manage the compilation and validation of models published on the Qualcomm AI Hub.
  • Build automated CI/CD evaluation harnesses to scale model onboarding and validation.
  • Author technical documentation, tutorials, and example notebooks for the developer community.

What we're looking for

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of relevant engineering experience.
  • Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of relevant engineering experience.
  • PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of relevant engineering experience.
  • 3+ years of industry experience in ML infrastructure, compiler engineering, or AI framework development (preferred).
  • Proficiency in Python and C++ (preferred).
  • Solid understanding of ML compiler concepts and hands-on experience with MLIR, ONNX, or TVM (preferred).
  • Experience with PyTorch model export and on-device deployment frameworks like LiteRT, ExecuTorch, or ONNXRuntime (preferred).
  • Experience building automated CI/CD pipelines for model compilation and validation at scale (preferred).

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