Senior Controls Engineer 

Parallel is seeking a Senior Controls Engineer with deep expertise in control systems development to join our engineering team. This role focuses on modeling, simulating, and designing the software that controls the electrical and mechanical systems on our rail vehicles, and on proving that software out in simulation before it reaches hardware. The ideal candidate has a strong foundation in control systems theory, extensive experience using simulation to develop and verify controllers, and a proven track record of delivering high-quality, real-time control software. 

Responsibilities

• Develop and maintain plant models of vehicle dynamics, powertrain, and braking systems, and use them to analyze, simulate, and tune controllers in tools such as MATLAB/Simulink or Python 
• Design and implement control algorithms for vehicle systems, validating them in simulation before deployment to embedded targets 
• Build and own simulation infrastructure, including model-in-the-loop (MIL), hardware-out-of-the-loop (HOOTL) and hardware-in-the-loop (HITL) environments, used to verify control software ahead of vehicle testing 
• Use modeling and simulation to derive sensor and actuator requirements that meet system performance needs 
• Correlate simulation results against test and field data to validate and improve model fidelity 
• Support system integration and vehicle testing, using simulation to reproduce and debug issues observed on hardware 
• Ensure high reliability, safety, and performance in all control software implementations 

What Success Looks Like 

• In 30 days: You have defined requirements and an architecture for the platooning simulation suite. You have run the existing code and have developed a feature roadmap to achieve the analysis goals required for the project 
• In 60 days: You have implemented the simulation MVP and are running real test cases. You have evaluated the baseline assumptions of our platooning model and have identified improvements to the controls stack to achieve better performance. 
• In 90 days: You have used the HOOTL simulation to drive performance upgrades in the controls stack and have implemented the onboard features required for real-world testing. You are running a test campaign using real Parallel vehicles to validate the outputs of the model and ground our software stack 

Basic Qualification

• Bachelor’s or Master’s degree in Electrical Engineering, Mechanical Engineering, Software Engineering, Mathematics, or a related field 
• 5+ years of experience developing control software for physical systems, with substantial time spent in modeling and simulation 
• Strong understanding of control theory, including PID, state-space, observers, system dynamics, and system identification 
• Proficiency in C/C++, Python, or similar languages used in both simulation and embedded systems development 
• Proficiency with modeling and simulation tools such as MATLAB/Simulink, Isaac Sim or equivalent Python-based frameworks, and with MIL, SIL, and HIL testing workflows 

Preferred Qualifications

• Experience building simulation infrastructure, digital twins, or automated simulation-based regression testing for control software 
• Distributed or multi-agent control: string stability, cooperative adaptive cruise control (CACC), or similar.
• State estimation (Kalman filtering, sensor fusion) and system identification from field data.
• Robust control, or hybrid systems that combine continuous dynamics with discrete events like contact and impact.
• NVIDIA Isaac Sim, Omniverse, or similar simulators such as Gazebo, MuJoCo, or Drake.
• Familiarity with embedded platforms (e.g., ARM Cortex, DSPs, RTOS-based systems) 
• Exposure to the automotive, aerospace, or robotics industries 
• Experience developing with Rust, especially in embedded platforms 
• Experience modeling and simulating vehicle dynamics, braking systems, electric powertrains, or sensor fusion 
• Prior ownership of a controls project from modeling and simulation through implementation, testing, and deployment