ADAS Test Engineer

Job Responsibilities

1. Testing and Validation:
   • Design, execute, and document tests for ADAS functionalities (e.g., adaptive cruise control, lane departure warning, emergency braking, etc.).
   • Conduct simulation-based and real-world vehicle tests to evaluate system performance.
   • Debug and troubleshoot system failures and inconsistencies.
2. System Analysis:
   • Analyze sensor data (radar, LiDAR, cameras, etc.) to ensure the accuracy and reliability of ADAS components.
   • Perform data logging and analysis to validate sensor fusion algorithms.
3. Collaboration:
   • Work with hardware, software, and systems engineering teams to identify and resolve issues.
   • Interface with cross-functional teams to understand system requirements and improve ADAS functions.
4. Regulatory and Compliance Testing:
   • Ensure compliance with industry standards, safety regulations, and quality benchmarks.
   • Document test results and provide technical reports for certification purposes.
5. Tools and Frameworks:
   • Utilize tools like MATLAB, Simulink, CANalyzer, CANoe, or similar platforms for analysis and testing.
   • Manage testing tools and environments, including driving simulators and test tracks.
6. Continuous Improvement:
   • Propose system enhancements based on test results and user feedback.
   • Stay updated with emerging ADAS technologies and trends.

Qualifications

• Education:
  • Bachelor’s or Master’s degree in Electrical Engineering, Automotive Engineering, Computer Science, or a related field.
• Experience:
  • 1–3 years of experience in automotive testing or ADAS development (preferred for junior roles).
  • Knowledge of automotive standards like ISO 26262, AUTOSAR, etc.

Required Skills

1. Technical Expertise:
   • Familiarity with ADAS technologies (radar, LiDAR, cameras, etc.) and their integration.
   • Experience with Vehicle Dynamics and Control Systems.
2. Programming:
   • Proficiency in scripting and programming languages such as Python, C++, or MATLAB.
3. Testing Knowledge:
   • Hands-on experience with testing tools like CANalyzer, CANoe, dSPACE, or NI LabVIEW.
   • Knowledge of hardware-in-the-loop (HIL) and software-in-the-loop (SIL) testing methodologies.
4. Problem-Solving:
   • Strong analytical skills to diagnose and resolve complex issues.
5. Soft Skills:
   • Excellent communication skills for reporting findings and collaborating with teams.
   • Strong attention to detail and a proactive approach.

Preferred Qualifications

• Familiarity with automated driving technologies.
• Knowledge of cloud-based data analysis or machine learning in ADAS contexts.
• Experience working with OEMs or Tier-1 automotive suppliers.