Lead Control System Engineer

Control System Engineer

Key Responsibilities

• Design, develop, and tune closed-loop control algorithms (PID, state-space, adaptive, etc.) for real- time embedded systems.
• Develop control software in C/C++, Python, or MATLAB/Simulink for deployment on microcontrollers or embedded Linux platforms.
• Simulate and validate control models using MATLAB/Simulink or equivalent tools before deployment.
• Integrate control systems with sensors, actuators, and real-time data acquisition systems.
• Collaborate with embedded software and hardware teams to implement control logic on target hardware.
• Perform system identification, modelling, and plant parameter estimation.
• Optimize software and control performance for latency, stability, and robustness.
• Participate in code reviews, test strategy development, and system debugging.
• Document algorithms, interfaces, and tuning processes thoroughly.
  

Required Qualifications

• Bachelors or Masters degree in Control Systems, Electrical Engineering, or a related field.
• 10+ years of experience in control systems engineering with embedded or real-time systems.
• Strong understanding of control theory (PID, LQR, observers, Kalman filters, etc.).
• Proficiency in programming languages: C/C++, MATLAB/Simulink, and Python.
• Hands-on experience with embedded systems (e.g., ARM Cortex-M/R, DSPs, FPGAs).
• Experience with real-time operating systems (RTOS) or bare-metal systems.
  

Preferred Qualifications

• Experience with model-based design (MBD) workflows and auto-code generation using Simulink.
• Familiarity with signal processing, estimation, and sensor fusion.
• Experience with control systems in robotics, automotive (e.g., motor control, chassis control), or power electronics.
• Understanding of CAN, SPI, I2C, and other real-time communication protocols.
• Exposure to version control systems (Git), CI/CD pipelines, and test automation.
• Familiarity with safety-critical software standards (e.g., ISO 26262, DO-178C) is a plus.
  

Soft Skills

• Strong analytical and mathematical skills.
• Effective communication and documentation skills.
• Collaborative mindset with cross-functional teams.
• Ability to balance theoretical and practical engineering approaches.
  

Tools Technologies

• MATLAB/Simulink, Control System Toolbox
• Embedded C/C++, Python
• RTOS platforms (e.g., FreeRTOS, Zephyr)
• Version control (Git), JIRA, Confluence
• Hardware-in-the-loop (HIL) simulation platforms