below marketmost similar roles pay hereabove market
This role pays more than
78%
of similar roles. Most pay
$161,975–$241,750
— the blue band above.
At the midpoint, this role pays about
$243k
versus about
$202k
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.
The AI Performance Engineer (Cloud AI Engineering), Sr | Staff | Sr. Staff joins the Machine Learning Engineering team to develop hardware and software solutions for Inference Acceleration. This role spans the full product lifecycle, requiring the candidate to convert, optimize, and deploy models for efficient inference. Key responsibilities include performance analysis of LLM, VLM, and diffusion models to scale throughput and latency, as well as designing high-level kernels in Triton. The engineer will map next-generation AI workloads onto hardware designs and collaborate with compiler and firmware teams. Required skills include Python, PyTorch, ONNX, and deep knowledge of transformer architectures, attention mechanisms, and distributed systems. The work focuses on solving complex performance and stability issues within the domain of Cloud AI and Deep Learning.
Convert, optimize, and deploy models for efficient inference using PyTorch and ONNX.
Analyze and optimize performance for LLM, VLM, and diffusion models to meet throughput and latency constraints.
Map next-generation AI workloads onto current and future hardware designs.
Design and implement high-level kernels in Triton to generate efficient, low-level code.
Identify new optimization opportunities by analyzing advanced GenAI algorithms like attention mechanisms and MoEs.
Analyze complex performance or stability issues to identify and resolve root causes.
Create engineering solutions to provide continuous insights into the performance of AI workloads.
What we're looking for
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware, Software, or Systems Engineering experience.
Master's degree in Computer Science, Engineering, Information Systems, or related field and 5+ years of Hardware, Software, or Systems Engineering experience.
PhD in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware, Software, or Systems Engineering experience.
Hands-on experience building and optimizing language models using PyTorch and ONNX, preferably in production-grade environments (preferred).
Deep understanding of transformer architectures, attention mechanisms, and performance trade-offs.
Experience in workload mapping strategies involving sharding or various parallelisms.
Strong Python programming skills and understanding of computer architecture, ML accelerators, and distributed systems.
Background in neural network operators, machine learning compilers, and torch.compile or torchDynamo (preferred).
Python
SQL
PowerShell
Windows
BIOS
ETW
Windows Performance Toolkit
Power BI
Tableau
Excel
Cinebench
3DMark
PCMark
Hardware Configuration
Lab Automation
Data Visualization