Autonomous Driving Map & Localization System Developer (J11423)

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四川滨江地产发展有限公司

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Autonomous Driving Map & Localization System Developer (J11423)

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workFull time

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GISLiDARPythonUTM

About The Role

Company: Sichuan Binjiang Property Development Co., Ltd. Job Description (Source: Liepin)

Responsibilities: Design the technical framework for integrated localization systems. Break down localization accuracy requirements. Develop integrated localization algorithms. Select and evaluate localization hardware. Develop map data and map EHP/EHR (Error Horizontal/Vertical) models for localization. Implement global path planning algorithms. Define and evaluate map performance metrics. Assess and optimize localization performance.

Qualifications: Minimum 2 years of experience in integrated localization (e.g., GNSS/INS, visual-inertial, lidar-based) for autonomous driving or related domains. Exceptional candidates may be considered with less experience or non-traditional backgrounds. Familiarity with lateral and longitudinal map feature matching methods and perception principles of localization features. Solid understanding of Bayesian theory and practical application of Kalman filtering, particle filtering, and other probabilistic estimation techniques. Proficiency in coordinate transformation calculations (e.g., Earth-Centered Earth-Fixed Local Tangent Plane). Hands-on experience developing integrated localization systems for autonomous vehicles. Strong GIS knowledge, including common geographic coordinate projection systems and transformations (e.g., UTM, Gauss-Kruger). Experience with automotive map data formats such as OpenDRIVE and NDS. Familiarity with ADASIS v2/v3 protocols for map data exchange. Prior experience developing EHR (Error Horizontal/Vertical) models. Knowledge of global path planning algorithms (e.g., Dijkstra, A*). Experience applying high-precision (HD) maps in autonomous driving systems. Ability to quickly reproduce state-of-the-art (SOTA) research paper results. Proficiency in C/C++ or Python, with proven software engineering experience. Experience developing with ROS (Robot Operating System) or other real-time operating systems. Strong coding standards, clean code practices, and good software engineering habits.

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四川滨江地产发展有限公司

Leading-edge innovations and technical excellence in the geospatial domain.

About The Role

Company: Sichuan Binjiang Property Development Co., Ltd. Job Description (Source: Liepin)

Responsibilities: Design the technical framework for integrated localization systems. Break down localization accuracy requirements. Develop integrated localization algorithms. Select and evaluate localization hardware. Develop map data and map EHP/EHR (Error Horizontal/Vertical) models for localization. Implement global path planning algorithms. Define and evaluate map performance metrics. Assess and optimize localization performance.

Qualifications: Minimum 2 years of experience in integrated localization (e.g., GNSS/INS, visual-inertial, lidar-based) for autonomous driving or related domains. Exceptional candidates may be considered with less experience or non-traditional backgrounds. Familiarity with lateral and longitudinal map feature matching methods and perception principles of localization features. Solid understanding of Bayesian theory and practical application of Kalman filtering, particle filtering, and other probabilistic estimation techniques. Proficiency in coordinate transformation calculations (e.g., Earth-Centered Earth-Fixed Local Tangent Plane). Hands-on experience developing integrated localization systems for autonomous vehicles. Strong GIS knowledge, including common geographic coordinate projection systems and transformations (e.g., UTM, Gauss-Kruger). Experience with automotive map data formats such as OpenDRIVE and NDS. Familiarity with ADASIS v2/v3 protocols for map data exchange. Prior experience developing EHR (Error Horizontal/Vertical) models. Knowledge of global path planning algorithms (e.g., Dijkstra, A*). Experience applying high-precision (HD) maps in autonomous driving systems. Ability to quickly reproduce state-of-the-art (SOTA) research paper results. Proficiency in C/C++ or Python, with proven software engineering experience. Experience developing with ROS (Robot Operating System) or other real-time operating systems. Strong coding standards, clean code practices, and good software engineering habits.