Reality Labs (RL) Sensors Team at Meta is helping build novel products in Augmented and Virtual Reality. Our team explores, develops, and delivers new cutting-edge sensing technologies that serve as the foundation of current and future AR/VR products at Meta. We are looking for candidates with experience in state estimation and sensor fusion to assist with the development of novel hardware and software systems within the RL Sensors Team, while collaborating with experts across multiple domains.
Research Scientist, Motion Sensors Responsibilities:
- Collaborate with other researchers and engineers across Meta to develop novel hardware and software products that advance the state-of-the-art in AR/VR systems.
- Collaborate with internal and external research, design, and engineering teams to develop state estimation and sensor fusion algorithms for sensor systems that advance the state-of-the-art.
- Work with the team to help design, setup, and run practical experiments related to sensor systems.
- Communicate results, trade-offs, decision points, and timelines to key internal and partner stakeholders.
- MS degree in Computer Science, Electrical Engineering, Mechanical Engineering, or related engineering disciplines.
- 4+ years' industry experience, directly contributing to design, modeling, and implementation of sensor fusion algorithms such as Kalman Filters.
- Experience in software development using C/C++ and scripting languages such as MATLAB or Python.
- Demonstrated experience in signal conditioning, digital filtering, detection and estimation theory.
- Demonstrated interpersonal experience in cross-group and cross-culture collaboration.
- Hands-on experience in developing algorithms for Inertial Sensors, Pressure Sensors, Magnetometers, Ultrasonic Transducers, and/or similar sensors.
- Proven track record of achieving significant results as demonstrated by first-authored publications or implementation of substantial software systems.
- Familiarity with the emerging Augmented Reality and Virtual Reality technologies.
- High levels of creativity and quick problem-solving skills.
- PhD degree in Computer Science, Electrical Engineering, Mechanical Engineering or related engineering disciplines.
- Experience with kinematic and dynamic modeling.
- Hands-on experience with Simultaneous Localization and Mapping (SLAM) and Visual Inertial Odometry (VIO).
- Familiarity with modern Machine Learning algorithms, specifically Deep Convolutional Networks, Recurrent Neural Networks, Clustering, and Dimensionality Reduction.
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