The Automated Driving Engineer leads the delivery of ADAS related functions—covering requirements capture, algorithm design, calibration, integration, verification, and continuous performance upgrade through data closed‑loop. The role bridges concept to SOP, ensuring each function meets safety, quality, and customer experience targets while adhering to ASPICE and ISO 26262 processes.

Education Qualification

Bachelor’s degree or above

No. of Years of Experience

3+ years of related experience in automotive development

Professional Exposure (Technical Skills)

Successfully delivered mass‑production L2/L2+ functions;  experience with CI/CD, Jenkins, ASPICE SWE.1‑SWE.6, automated regression frameworks;  exposure to map‑based ADAS a plus.

Functional Skills

Familiar with Matlab, Simulink. System thinking, root‑cause analysis, statistical data analysis, clear technical writing and presentation.

Behavioral Skills

Self‑driven, proactive problem solver, strong communication, ability to work cross‑functionally in global teams.

Special Knowledge and Skills Required

Knowledge of ISO 26262, UN‑R79/152 and China ICV data regulation.

Any Others

Ability to manage multiple tasks and prioritize effectively in a fast-paced environment;  Global and local Product Development (PD) teams, Tech planning, etc;  Global and local partnerships including vendors, suppliers, academics, and government agencies.

Key Responsibility:

Analyze system requirements and translate them into detailed feature and software specifications for L2 and adventure features.  Design and implement control algorithms in Matlab/Simulink with auto‑coding or in embedded C, ensuring MISRA and modeling guidelines compliance.  Plan and execute calibration activities (bench, SIL, vehicle) to achieve KPI such as TTC accuracy, lateral/longitudinal control error, comfort and robustness over corner‑cases.  Integrate generated code into dSPACE Autobox and production ECUs; manage build, flashing, and configuration control. Develop comprehensive verification plans and conduct SIL, proving‑ground and on‑road tests; diagnose issues, implement fixes and regression tests.  Establish data pipelines, perform statistical analysis using Python/Matlab, and release builds via data closed‑loop platform to continuously improve performance.  Contribute to DFMEA, FUSA, SOTIF and homologation documentation; support system and vehicle sign‑off.  Foster best practices, and actively participate in design and code reviews.