At Reality Labs Research (RL-R), our goal is to explore, innovate and design novel interfaces and hardware subsystems for the next generation of virtual, augmented, and mixed reality experiences. Mixed and augmented reality (XR) devices blur the boundaries between the physical and the digital worlds, resulting in user inputs that are noisy and unreliable and an interaction environment that is not fully known to the system. And yet these devices can display information to the user in a low-friction manner that is more tightly coupled to one's body and the physical environment, exposing the opportunity for persistent "always-on" assistance. We argue that to build effective XR interactions, we must (1) reduce system uncertainty by understanding the user and environment, and (2) effectively adapt the interface to engage the user in uncertainty reduction and to allow for online learning and personalization. Modern methods in AI and machine learning are important to achieve these goals. We are looking for a talented Research Scientist with expertise and passion for building intelligent systems to join Reality Labs' research organization. Ideal candidates will have a passion for the intersection of science, design, and engineering and expertise with computational and machine learning methods. Researchers will have the opportunity to publish in peer-reviewed conferences and journals and are expected to effectively collaborate with cross-disciplinary experts, including applied machine learning, electrical, mechanical, and software engineering, perceptual science, and design.

• Design, build and test machine learning systems that improve human-computer interaction with the real world (eg., real-time pose estimation, hand-object recognition, cognitive state recognition).
• Work collaboratively with other scientists and designers to (1) develop novel models of eye gaze behaviour, and/or (2) advance research in machine learning methods for intelligent interfaces for augmented reality.
• Publish and present papers at international conferences and journals and attend top conferences in the field.

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• PhD in the field of computer vision, machine learning, artificial intelligent, human-computer interaction, computational neuroscience, computer science, or related field.
• 3+ years of experience building ML solutions for challenging real-world interactive applications and proving them through end-to-end prototypes and/or products.
• 3+ years of experience in at least one deep-learning software library (e.g., PyTorch, Caffe2, TensorFlow), including formulation, training, and evaluation of new algorithms and writing reusable modules.
• Track record of achieving research results and innovation as demonstrated by first-authored publications and/or patents.

• Experience with hand, eye, and/or body tracking.
• Experience with multimodal modeling, embeddings, and/or time-series modeling.
• Experience designing data-collection protocols and recording datasets for machine-learning systems.