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Our org owns Meta's hardware tech strategy for AI - finding innovative hardware for GPUs and Meta's custom AI chips, as well as CPU, memory, and storage as well as getting these to work in Meta's
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, telemetry systems) into immersive environments. Optimize XR applications for performance including CPU/GPU profiling, draw call reduction, shader optimization, memory management, and LOD systems. Develop
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of maintaining research-related application software such as Qualtrics, SPSS, MAXQDA, Wmatrix, NVivo, Comprehensive Meta-Analysis (CMA), etc; (e) have excellent interpersonal, communication, and technical
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approaches, the application of meta learning, and the integration of convex optimization layers Increase inference efficiency (e.g., GPU acceleration) and assess the applicability domain of learned algorithms
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Engine, Unity, Blender, Adobe Creative Cloud, or DaVinci Resolve, with simple version-control tools like GitHub or Perforce. Experience with powerful PCs with strong GPUs, a mix of VR headsets like Meta
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complexities and assess its convergence in inference Investigate scaling and performance bottlenecks Explore hybrid ML-classical approaches, the application of meta learning, and the integration of convex
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Engine, Unity, Blender, Adobe Creative Cloud, or DaVinci Resolve, with simple version-control tools like GitHub or Perforce. Experience with powerful PCs with strong GPUs, a mix of VR headsets like Meta