Parallel Systems is pioneering autonomous battery-electric rail vehicles designed to transform freight transportation by shifting portions of the $900 billion U.S. trucking industry onto rail. Our innovative technology offers cleaner, safer, and more efficient logistics solutions. Join our dynamic team and help shape a smarter, greener future for global freight.

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