Senior Control System Engineer (Autonomous Driving)

42dot is seeking a Senior Control System Engineer for Autonomous Driving to develop advanced control systems to solve complex and challenging problems in the field of autonomous driving. You will work with experts in motion planning, functional safety, hardware engineering, and related fields to develop robust and reliable autonomous driving systems. You will lead the integration of various control algorithms and performance improvements, and guide the engineering team.

Responsibilities:

• Lead the design, implementation, and optimization of longitudinal and lateral control systems for autonomous driving.
• Oversee the design and implementation of low-level control systems that translate high-level commands into specific actuator controls for real-time autonomous driving tasks.
• Develop and optimize estimation algorithms for key vehicle parameters such as road slope, vehicle speed, and slip to improve the precision and reliability of control systems.
• Work closely with teams focusing on motion planning, behavior planning, and mission planning to ensure smooth system integration.
• Provide guidance on control architecture and system optimization, and mentor junior engineers.

Qualifications:

• Bachelor's/Master's degree in Robotics, Electrical Engineering, Mechanical Engineering, Computer Science, or related field.
• 5+ years of experience in control system design, especially in autonomous vehicles or similar fields.
• Strong expertise and practical experience in robust control, vehicle dynamics, and systems engineering.
• Practical experience with system interference observation, system identification, and state estimation techniques such as Kalman filters and particle filters.
• Proven experience with actuator control in low-level control systems.
• Proficiency in C++, Python, or equivalent programming languages.
• Experience working in safety-critical environments with real-time control systems.

Preferred Qualifications:

• Experience with ROS/ROS2 and integration with autonomous driving systems.
• Experience with Model Predictive Control (MPC) and nonlinear control systems.
• Experience with industry standards and safety-critical systems in automotive or aerospace fields.
• Experience with adaptive and self-calibrating control algorithms to maintain and improve system performance under various conditions.
• Knowledge of source control management, build processes, code review, and testing methodologies.
• Demonstrated technical capability through published research work in relevant fields.

Interview Process:

1. Document screening
2. Coding test
3. Video interview (about 1 hour)
4. Face-to-face or video interview (about 3 hours)
5. Final selection

The interview process may vary by position and may change depending on schedule and circumstances. Interview schedules and results will be communicated individually via the email registered in your application.