Reality Labs Research (RL-R) brings together a world-class R&D team of researchers, developers, and engineers with the shared goal of developing XR and AI across the spectrum. The Surreal research group at RL-R is seeking exceptional engineers to solve the next generation of research challenges on the path to building future machine perception enabled technologies. We are looking for talented engineers to architect and build the next-generation research device of Project Aria. We are building this research device to understand the world from a human’s perspective and lay the foundation for Contextual AI experiences on future AI & AR glasses.In this role you will design, analyze, and optimize the performance of Contextual AI algorithms on the next-generation Aria prototype. You will focus initially on low-power on-device custom compute implementations, and then extend the optimization to the phone and cloud-based processing chains.

MINIMUM QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Significant experience in one or more of the following areas: embedded systems, real-time systems, artificial intelligence, machine learning, robotics, computer vision
• Significant experience in programming languages with a technical background
• Proven track record of planning multi-year roadmap in which shorter-term projects ladder to the long-term vision
• Significant experience in mentoring/influencing engineers across organizations
• 12+ years of experience coding experience in C, C++ and/or Python

PREFERRED QUALIFICATIONS:

• Doctor of Philosophy (Ph.D.) in Computer Engineering, Computer Science, or Electrical Engineering and Computer Sciences
• Expertise in Physics, Optics, Computer Vision, Robotics, Sensor Fusion, or Machine Learning
• Experience in shipping computer vision or image processing products to millions of customers or have started a new line of product
• Experience in rapid prototyping of systems that span devices and backend services

• Analyze and optimize real-time computer-vision and machine learning algorithms across a heterogeneous compute fabric in a custom Meta system-on-chip
• Technically lead in a team environment across multiple scientific and engineering disciplines, making the architectural trade-offs required to rapidly deliver software solutions
• Effectively communicate complex features and systems in detail
• Learn constantly, dive into new areas with unfamiliar technologies, and embrace the ambiguity of real-time Contextual AI research
• Debug complex problems that span multiple compute systems
• Globally optimize system performance under multiple constraints of low power, low latency, and limited memory