This role pays more than
98%
of similar roles. Most pay
$176,937–$262,238
— the shaded band above.
At the midpoint, this role pays about
$352k
versus about
$220k
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
613 open roles
on FindRole.
Listed pay typically runs
$155,400–$232,800
across 594 roles with salary data.
Senior Director of Engineering - AI Platform leads a global organization focused on AI systems, model enablement, and software integration for Snapdragon Compute platforms across Windows, Android, and Linux environments. This leader defines the company's AI software strategy, overseeing NPU, GPU, and CPU optimization to deliver advanced experiences in generative, multimodal, and agentic AI. The role involves managing end-to-end software enablement, including model quantization, deployment frameworks, and developer tooling while driving strategic partnerships with Microsoft and other industry leaders. Key technical requirements include expertise in machine learning frameworks like TensorFlow, PyTorch, and Keras, as well as proficiency in Python, C, and C++. The position addresses the challenge of optimizing high-performance AI workloads on heterogeneous compute architectures, ensuring superior performance across various benchmarks while managing complex cross-functional dependencies between silicon, firmware, and software.
Define and execute the AI software strategy for Snapdragon platforms across Windows, Android, and Linux systems.
Lead technical engagement and co-engineering activities with Microsoft to develop features like Copilot+ and WinML.
Manage the optimization of AI workloads across heterogeneous compute architectures including NPU, GPU, and CPU.
Oversee model enablement tasks such as quantization, validation, and deployment for generative and multimodal AI.
Establish benchmarking strategies and performance targets to ensure market leadership in AI capabilities.
Build and lead a global engineering organization by recruiting talent and mentoring technical leaders.
Manage cross-functional dependencies across silicon, firmware, and software to ensure timely product delivery.
What we're looking for
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field with 10+ years of experience in Hardware, Software, or Systems Engineering.
Master's degree in Computer Science, Engineering, Information Systems, or related field with 9+ years of experience in Hardware, Software, or Systems Engineering.
PhD in Computer Science, Engineering, Information Systems, or related field with 8+ years of experience in Hardware, Software, or Systems Engineering.
5+ years of experience with Machine Learning frameworks such as TensorFlow, Caffe, PyTorch, or Keras (preferred).
5+ years of experience with low-level interactions between operating systems and hardware (preferred).
5+ years of experience in embedded system development and optimization for ML domains like NLP or multi-media (preferred).
10+ years of experience with programming languages suitable for machine learning such as Python, R, C, or C++ (preferred).
8+ years of experience using statistics and probability, technical leadership, large matrixed organizations, senior leadership interaction, and managing budgets (preferred).
TensorFlow
PyTorch
Python
C++
GPU
NPU
Windows
High Performance Computing
Parallel Computing
Machine Learning
Computer Vision
Generative AI
Agentic AI
Hardware Acceleration
Agile
Version Control
Computer Vision
Deep Learning
Python
C++
PyTorch
TensorFlow
Keras
Caffe
Linux
Android
QNX
Quantization
Pruning
Distillation
CPU
GPU
DSP
NPU
Containerization