Jobs at Qualcomm

Lead architecture, design, and development of XR platform software (AR/VR/MR) on Snapdragon platforms, working across system architecture, embedded software, graphics, AI/ML, and computer vision. Translate product requirements into implementation specifications, drive architectural trade-offs for performance and power efficiency, and provide technical leadership across multiple teams. Requires strong C++ proficiency, experience with heterogeneous computing systems (CPUs, GPUs, DSPs, AI accelerators), Android/Linux embedded platforms, and 8+ years of software engineering experience.

As an AI Software Engineer at Qualcomm, you will develop and optimize machine learning software for the Qualcomm AI Stack (QAIRT and Genie SDKs), enabling efficient execution of large language models and deep neural networks on Snapdragon platforms. You will validate and optimize performance of generative AI models, debug complex issues, and collaborate across teams to deliver robust AI solutions. The role requires strong software design, programming, and debugging skills, with expertise in machine learning frameworks, embedded systems optimization, and languages like Python or C++. You will work with minimal supervision, participate in design reviews, and contribute to a culture of technical excellence.

Qualcomm seeks a Principal Engineer to lead the architecture, design, and development of XR platform software (AR/VR/MR) on Snapdragon platforms. The role requires deep expertise in C++, heterogeneous computing (CPUs, GPUs, DSPs, AI accelerators), Android/Linux embedded systems, and system-level performance optimization. Responsibilities include defining platform requirements, conducting architecture trade-offs for power/latency/performance, collaborating with computer vision and AI/ML teams, and driving technical decisions across multiple product areas. The ideal candidate brings commercial product experience and expertise in computer vision, graphics, SLAM, sensor fusion, or XR frameworks.

Design and develop the end-to-end compilation pipeline for Qualcomm AI Hub, handling PyTorch and ONNX model ingestion, graph optimization, and deployment across CPU, GPU, and NPU backends on Snapdragon SoCs. Own compilation infrastructure, ONNX-based and PyTorch compilation paths, ONNXRuntime QNN execution provider contributions, and tooling for profiling and debugging. Scale model onboarding through automated CI/CD pipelines and partner with internal teams to translate deployment constraints into compilation strategies. Build developer-facing diagnostics, documentation, and tutorials for the AI Hub community.

Digital Test Engineers will create test solutions for Qualcomm silicon validation, characterization, and manufacturing enablement across microprocessors, high-speed I/O, logic, and memory IP. The role involves hands-on work with test equipment (oscilloscopes, spectrum analyzers, logic analyzers, network analyzers), signal integrity analysis, and development using Python, Java, and Linux. Candidates will support product introduction across multiple specializations including DFT/yield management, AI/ML-driven test development, and emerging areas like 2.5D/3D IC testing and photonic integrated circuits. The position requires a Bachelor's degree in Engineering or related field and 3+ years of hardware engineering experience.

Qualcomm is seeking a Software Engineer for their Power and Limits management group to develop firmware and software solutions for chipsets across multiple subsystems. The role involves analyzing requirements, designing robust software architectures, performing detailed performance/power analysis, and developing profiling and debugging tools for silicon validation. Candidates will work across system, power, software, and hardware teams to optimize power efficiency, thermal performance, and execution efficiency from pre-silicon through commercialization, with exposure to ARM architecture, real-time operating systems, and machine learning applications.

Design, develop, and deploy end-to-end generative AI solutions including GenAI agents, LLMs, and applications to solve complex business challenges. Build data pipelines, design APIs for AI accessibility, and collaborate with cross-functional teams (developers, data scientists, business) to implement enterprise GenAI solutions. Requires 4+ years of full-stack application development (Java, Python, JavaScript) and 3+ years with data structures, algorithms, and data stores. Stay current with AI research and communicate technical concepts to non-technical stakeholders.