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Harbinger Motors Inc.

Firmware Engineer (Bare-Metal / RTOS)

Garden Grove, CAFrom $160kmidAdded today

About this role

Harbinger seeks a Firmware Engineer to develop bare-metal and RTOS-based firmware for electric vehicle motor control systems. You'll design deterministic, high-performance embedded software that balances safety, efficiency, and nanosecond-level precision while working closely with hardware and controls teams.

What you'll do

  • Design and implement deterministic firmware for EV motor control in bare-metal and RTOS environments
  • Configure Board Support Packages (BSPs) and develop low-level hardware drivers for optimal performance
  • Deploy and optimize complex control algorithms including Field-Oriented Control (FOC)
  • Enhance CPU efficiency, reduce interrupt latency, and optimize memory footprints
  • Conduct rigorous testing and validation using real-time simulation and Hardware-in-the-Loop (HIL) environments
  • Collaborate with hardware, software, and power electronics teams for system integration

What they're looking for

  • C/C++ for embedded systems
  • ARM Cortex-M microcontroller development
  • Bare-metal and RTOS firmware architecture
  • Motor control algorithms and Field-Oriented Control (FOC)
  • Digital signal processing (DSP) and control theory
  • Hardware debugging and real-time systems
  • Communication protocols (CAN, SPI, UART)
  • Hardware-in-the-Loop (HIL) testing
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Harbinger Motors Inc.

Harbinger Motors Inc. develops medium-duty electric vehicles and related powertrain systems, with a focus on commercial delivery trucks and advanced driver-assistance capabilities. The company is hiring engineers across manufacturing, thermal analysis, systems architecture, quality assurance, and software testing to build out its EV platform and autonomous driving features.

Website
harbingermotors.com
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Likely interview questions

  • Walk us through your experience developing deterministic firmware for real-time control systems and how you managed interrupt latency constraints.
  • Describe a complex motor control algorithm you've implemented—what were the key performance challenges and how did you optimize for CPU efficiency?
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