ADAS Driving System Verification Engineer 智能驾驶辅助系统测试验证工程师

Mercedes-Benz Group China Ltd.

Shanghai, No. 2069, Jin Xiu Dong Road, Jinqiao, Pudong District (Hybrid)

Job Type Full-time

Experience 3–5 years

Posted 1 month ago

Hybrid 3–5 years Level

Review ADAS function specifications with customer and market function owners for global and China markets.
Clarify the requirement scope to be tested in each release, focusing on driving functions such as ACC, ALSA, ALCA, L2+ and L2++.
Facilitate requirement reviews with China and global partners to ensure China-specific test contents are implemented.
Synchronize testing content and timelines with global test managers.
Design test cases, organize test-case reviews, prioritize test content and align test plans.
Assign test sets to appropriate test platforms and enable testing at the beginning of each release.
Define failure causes, report test results to project teams and function owners, and drive issue resolution.

Bachelor's degree or above in vehicle engineering, electrical engineering, robotics, computer science or a related field.
3–5 years of experience in vehicle EE, ADAS or CarIT-related areas.
Strong knowledge of ADAS driving functions and systems at signal and end-to-end system levels.
Practical experience with in-vehicle ADAS testing on real roads and proving grounds, including test driving, measurement setup, log capture and failure reproduction.
Experience with HIL test automation, test-script development, automated execution and CI/CD integration for ADAS regression testing.
Basic project-management and MS Office skills; ISTQB certification is beneficial.
Chinese native speaker with fluent English; German is beneficial.
Strong communication and teamwork skills in a global, multicultural environment.
Knowledge of vehicle perception and control systems, including powertrain, ESP and steering systems.
Hands-on engineering mindset, independent and proactive working style, and willingness to travel in China and abroad.
Familiarity with measurement devices such as CANoe, ABD and RTrange.
Knowledge of AI/ML fundamentals and hands-on experience with AI coding tools such as GitHub Copilot or LLM-assisted coding.