Meta Reality Labs Research (RLR) is dedicated to the research and development required to bring virtual and augmented reality to billions of people around the world. At our lab, we aspire to a vision of social VR and AR, where people are able to interact with each other across distances in a way that is indistinguishable from in-person interactions. Meta RLR is looking for a talented Research Engineer to accelerate the progression to authentic social presence in Virtual Reality and Augmented Reality. In this role, you will be a member of the Mobile Telepresence team which has been committed to comprehensive mobile optimization that delivers end2end telepresence with high energy efficiency. The mobile optimization including but not limited to neural network architecture innovation, model compression, and low bits inference for dedicated computing hardwares directly guides performance and deployment of telepresence solutions on future Meta ARVR products and push forward the State-of-the-art on mobile efficiency.
You will be working on designing novel model architecture with high hardware efficiency, standardizing optimization algorithms into mobile compiler and runtime engine, and creating tools/flow to accelerate telepresence deployment on the current & next generation of ARVR hardware platforms. You will work closely with AI and telepresence researchers to analyze telepresence algorithms (which are mixed operators of computer vision, deep learning models, and graphic rendering processing) and apply codesign methodologies from the early phase. You will also partner with software engineering teams to validate optimization solutions on ARVR hardware which has off-the-shelf SoCs and/or inhouse neural network accelerators. You will apply software development best practices to design features, optimization, and performance tuning techniques. You will gain valuable experience in developing product driven computing solutions and will help in driving next generation hardware software codesign for AI domain specific problems.