Build and maintain ML infrastructure: training pipelines, data workflows, model integration and serving, tooling for experimentation, optimization of data pipelines, and collaboration with researchers to productionize models.

Design and build a performant, cross-platform framework for sensing, detection, haptics, and ML inference. Develop runtime execution systems, hardware abstraction layers, developer APIs, and integrate cameras, microphones, and haptics while optimizing real-time performance and stability.