Staff SW Engineer, Constrained AI Software

Qualcomm•San Diego, CA

2d•$158,400 - $237,600

About The Position

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drive digital transformation, creating a smarter, connected future for all. As a Qualcomm AI Software Engineer, you will develop and implement cutting-edge machine learning techniques that enable the efficient utilization of state-of-the-art solutions across various technology verticals. In the AI Software team, we build the Qualcomm AI Engine to enable OEMs and developers to run their Machine Learning workloads on Qualcomm's low-power AI accelerators in a Constrained Operating Environment. Your work will directly impact the runtime efficiency, latency, and power consumption of AI applications running on Qualcomm hardware deployed on cars, notebook computers, phones, and wearables. Come join us to work on bleeding edge AI technology. At the Staff Engineer level, you will play a key role in shaping the technical direction of the Qualcomm AI Engine, working with a high degree of autonomy across complex runtime features and subsystems. You will drive architectural decisions that span multiple projects, partnering closely with hardware, systems, compiler, and product teams to deliver scalable, high‑performance solutions. In addition to hands‑on development, you will provide technical leadership through design reviews and mentorship, ensuring that our software meets demanding requirements for performance, power efficiency, and long‑term maintainability across Qualcomm’s low‑power AI platforms.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Nice To Haves

Master’s degree in Computer Science, Computer Engineering, or Electrical Engineering
3+ years of experience building embedded software applications.
Familiarity with various generative AI model architectures such as LLMs.
Strong understanding of hardware acceleration and deployment of generative AI inference at the connected edge.
Experience with Hexagon DSP SDK or cross compiler toolchains for embedded systems
Familiarity with TensorFlow, PyTorch or ONNX
Experience using/integrating Qualcomm AI Stack products (e.g. QAIRT, QNN, Genie).
Experience with development in various platforms such as Linux, Android, or Windows.
Knowledge of low-level interactions between operating systems (e.g., Linux, Android, Windows) and hardware.
Experience with CMake-based build environments.
Experience with agile software development practices and git-based SCM.
Ability to collaborate across a globally diverse team and manage multiple interests.

Responsibilities

Design and implement core components of the ML runtime framework for inference on Constrained AI systems, operating in low power, small memory footprint platforms
Develop and maintain C/C++ code for runtime kernels and system-level integration
Development of model analyzing tools for internal and external customers
Development and profiling of performance KPIs and footprint across AI workloads for platforms such as Android/Aluminum, Linux, QNX , Windows and future platforms
Track and adopt leading 3rd party compiler toolchains / packages across Qualcomm AI platforms/SoCs
Address issues found in existing and past Qualcomm AI products
Debug customer machine learning use cases executing on Qualcomm AI Stack
Communication across globally diverse team
Participate in software quality process improvements