Senior Edge ML Engineer – On-Device AI

QUALCOMM, Inc.; San Diego (CA); On-site; USD 194,000 - 292,000; Full time

Job summary

Qualcomm AI Research is seeking talented AI software engineers to enable AI technologies on edge devices. You will join a high-caliber team building GenAI solutions with model optimization tools to deploy state-of-the-art models to edge devices with optimal power, memory, and computation use.

In this role, you will be part of a multi-disciplinary team that collaborates across hardware, software and systems and ships on Qualcomm AI accelerator engines for devices such as smartphones, autonomous

Qualifications

• 5+ years of experience with ML frameworks and Deep Learning (PyTorch).
• 5+ years of experience with Python, C, or C++ for ML.
• Strong software design, development and debugging skills.
• Knowledge of Android programming is a plus.
• Experience optimizing algebraic operations for HW cores is a plus.
• Knowledge of neural network training and quantization is a plus.
• Experience with Qualcomm QNN SDK is a plus.

Responsibilities

• Development of end-to-end embedded AI software to train and finetune neural network models on Qualcomm leading edge hardware with optimal resources.
• Design and enhance the implementation of ML/AI SW stack, kernels, and runtime software to improve performance and power efficiency.
• Collaborating with our AI Processor Hardware team to implement high-quality solutions for new ML operators/layers that optimally utilize new capabilities in next-gen AI processors.
• Development of debugging/profiling tools and user‑friendly SDKs for customers to foster rapid deployment of their new use cases.

Skills

ML frameworks

Deep Learning

Python

C/C++

Android

Algorithm optimization

Neural network training

Neural network quantization

QNNSDK

Education

Bachelor's degree in CS/Eng

Master's degree in CS/Eng

PhD in CS/Eng

Tools

QNNSDK

Job description

Qualcomm AI Research is seeking talented AI software engineers to enable AI technologies on edge devices. You will join a high-caliber team building GenAI solutions with model optimization tools to deploy state-of-the-art models to edge devices with optimal power, memory, and computation use.

In this role, you will be part of a multi-disciplinary team that collaborates across hardware, software and systems and ships on Qualcomm AI accelerator engines for devices such as smartphones, autonomous