Multimodal, always on perception and agentic AI are driving designs and adoption of new personal, wearable, and eXtended Reality platforms. Qualcomm's XR Labs team is seeking a skilled C++ and Machine Learning engineer to design and build software systems for distributed AI execution across interconnected wearable, XR, and companion devices. In this role, you will define the architecture, runtime behavior, and software interfaces that enable AI workloads to be coordinated across power-constrained personal devices, phones, and edge/server compute platforms. You will help design systems for workload distribution, device coordination, protocol design, multimodal data flows, and power/latency-aware execution, helping create next-generation personal experiences powered by collaborative AI. The job will involve researching, and evaluating available solutions, prototyping, and deploying them on our chipsets, as well as interfacing with HW, FW, and SW engineers as power-efficient implementation is being further optimized and integrated into our framework.

Understanding typical AI workloads dispatched across several device constellations and use cases.

Identify and evaluate suitable algorithms with an intimate understanding of performance/ requirements tradeoffs.

Define interfaces and coordination protocols for task routing, synchronization, and state exchange across devices.

Build, optimize, and evaluate multimodal sensing and inference pipelines, designing runtime policies for workload distribution based on latency, power, compute availability, etc.

Help integrate implementation into an existing XR/personal device framework, collaborating with AI, connectivity, and platform system engineers.

Document optimized design and benchmark resulting performance on target SoCs.