• Signal Processing: Design and implement algorithms to process raw sensor data, correcting for environmental attenuation, noise, and physical constraints • Sensor Fusion & Calibration: Develop techniques to fuse multi-modal sensor streams and perform precise sensor calibration to ensure data alignment and accuracy across the hardware stack • 3D Scene Reconstruction: Build pipelines that generate 3D representations of the environment from complex inputs • Feature Detection: Apply a combination of conventional and deep learning approaches to identify key features and objects within the sensor data • Production Engineering: Contribute to the production codebase, ensuring algorithms are scalable, robust, and well-tested in a primarily Python-based stack