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1. Test Strategic Planning and Direction Control
Formulate a future test strategy for autonomous driving by integrating system architecture development experience and clarify the 3-5-year test technology development direction based on in-depth analysis of technological trends, policies/regulations, and market demands in the autonomous driving industry. From a system architecture perspective, predict the testing strategy requirements brought by the iteration of intelligent driving systems, proactively lay out testing technologies and solutions, and ensure that testing strategies match the evolution of system architectures, with particular emphasis on the positioning and planning of simulation testing in the overall strategy.
2. Test System Construction and Optimization
Lead the establishment of a full-lifecycle testing system for intelligent driving, including simulation testing, hardware-in-the-loop testing, real-vehicle road testing, and other links, and optimize the connection logic of each link by leveraging system architecture development experience. Establish intelligent testing evaluation standards, design test indicators according to system architecture characteristics, ensure that test results accurately reflect system performance and potential risks, and improve testing effectiveness and efficiency. Focus on improving the processes and specifications of simulation testing in the entire testing system to enhance the coverage and accuracy of simulation testing.
3.Simulation Platform Development and Management
With system architecture development experience, lead the requirements analysis, architecture design, and functional development of intelligent driving simulation platforms to ensure the platforms have high scalability and stability. Continuously optimize simulation platform performance, enhance the realism and complexity of simulation scenarios, and achieve comprehensive simulation testing of modules such as perception, decision-making, and control in intelligent driving systems. Be responsible for the integration and docking of simulation platforms with other testing tools and systems, unblock data circulation channels, and build an integrated testing environment.
4.Simulation Test Scenario Construction and Optimization
Design and build a simulation test case library covering all scenarios of intelligent driving, including conventional road scenarios, extreme weather scenarios, complex traffic scenarios, etc., and use system architecture knowledge to manage scenarios in a hierarchical and categorized manner. Utilize data-driven and AI technologies to analyze actual road test data and publicly available industry data, mine potentially dangerous scenarios, and continuously update and optimize the simulation test scenario library to enhance the simulation testing capability of mimicking the real world.
5.Resource Integration and Collaborative Promotion
Integrate internal and external resources to promote the R&D and upgrading of intelligent driving testing platforms and toolchains and put forward requirements for testing platform functions and performance based on system architecture development experience. Coordinate multiple departments such as R&D, testing, and algorithms to promote the deep integration of testing strategies with system development processes and ensure the effective implementation and execution of testing strategies in projects. Particularly strengthen cooperation with algorithm teams to ensure that simulation testing can provide effective feedback for algorithm optimization.
6.Technological Innovation and Team Empowerment
Explore new technologies and methods for intelligent driving testing, such as virtual-scenario-based automated testing and AI-assisted testing and evaluate technological feasibility and application value by combining system architecture development experience. Provide technical guidance to testing teams, share system architecture knowledge and testing strategy formulation ideas, and improve the overall technical level and strategy formulation capabilities of the team. Regularly organize technical seminars and experience sharing on simulation testing to promote technological innovation in the field of simulation testing within the team.
? Bachelors Degree in automobile engineering, electric engineering, software engineering, machine learning, or similar majors, Master Degree preferred
? At least 8 years working experience in the ADAS system verification & validation and simulation solution(SiL/HiL,etc.) relevant areas
? Experience of OEM and Tier1 on ADAS development processes and development cycles, has 1 full project development cycle preferred
? Deep knowledge in ADAS system architecture on big model solution
? Deep knowledge in ADAS system verification & validation processes considering manual and automated testing
? Deep knowledge in ADAS simulation solution and digital twins trend for automobile industry
? Excellent project management skills and problems solving skills
? Excellent communication and organizational skills
? Team player with open-minded work attitude and ability to adapt to new situations
? Good command of spoken and written Chinese and English (German as a plus)