Develop end-to-end machine-learning models for autonomous-driving taxis from camera and LiDAR data, then evaluate and optimize them in simulation and real vehicles.
About this role
Localization Engineer on the Ground Truth team, supporting autonomous-driving software for a taxi service. Localization and Perception engineers share responsibility for reliable ground-truth data; this role spans collected-data quality checks, recognition-model labeling, and the position and pose estimates used by end-to-end models, Planning, and evaluation.
Work includes fusing GNSS, IMU, LiDAR, cameras, and wheel speed; state estimation, filter and error-model design, confidence outputs, intrinsic and extrinsic calibration, coordinate transforms, time synchronization, and corrections for vehicle noise, heat, and antenna characteristics. It also covers sensor-data quality and representation, processing pipelines, hard-example extraction, real-vehicle log and failure analysis, and interfaces with E2E training, simulation, and evaluation. No candidate qualifications or required experience are stated.
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