An Embedded Engineer at Brain plays a pivotal role in bridging the gap between cutting-edge autonomous software and physical hardware. Brain is a leader in robotic technology, powering autonomous mobile robots (AMRs) that navigate complex, real-world environments. The firmware and low-level software developed by this team form the nervous system of these machines, translating high-level artificial intelligence commands into precise, reliable physical movements.

In this role, you will work directly on the microcontrollers, sensor interfaces, and communication buses that allow robots to perceive their surroundings and operate safely. Because these machines operate in public spaces, the firmware you write must be highly performant, deterministic, and safe. A single bug could lead to operational failure, making rigorous engineering practices and a deep understanding of hardware constraints absolute necessities.

As a Software Engineer I, Firmware or Embedded Engineer, your contributions will directly impact the reliability of Brain's core product offerings. You will collaborate with hardware designers, systems engineers, and high-level software teams to bring up new custom boards, optimize power consumption, and ensure seamless communication across the entire robotic stack.

The technical screening process at Brain is designed to evaluate your fundamental understanding of hardware-software interactions, low-level data transmission, and debugging methodologies. The following questions represent patterns observed in actual interview loops for the Embedded Engineer position.

Serial Communication & Protocols

This category evaluates your understanding of how microcontrollers exchange data with sensors and peripheral devices, with a heavy emphasis on handling edge cases and data integrity.

• How would you design and implement a robust data receiver over UART?
• How do you distinguish between a complete and an incomplete packet if there is no length field in the packet header and no specified timeout?

Preparing for an interview at Brain requires a balanced approach that covers both theoretical embedded concepts and practical, hands-on debugging scenarios. You should approach your preparation with a focus on how software behaves under physical constraints.

Role-Related Knowledge – You must demonstrate a deep, intuitive understanding of low-level systems. This includes microcontroller architectures (specifically ARM Cortex-M), registers, memory-mapped I/O, and serial communication standards. Be prepared to explain not just how a protocol works, but why it might fail in a noisy physical environment.

Problem-Solving under Ambiguity – Interviewers at Brain frequently present open-ended debugging scenarios or protocol design questions. They want to see how you structure your thoughts when dealing with incomplete information. Rather than guessing, ask clarifying questions about hardware specs, timing constraints, and failure modes.

Hardware Empathy – A successful candidate must show that they respect the physical hardware. This means understanding timing diagrams, signal integrity, power budgets, and how to use tools like logic analyzers and oscilloscopes to verify that your software is behaving correctly on the physical board.

The interview loop for an Embedded Engineer at Brain typically progresses from initial conversations to practical coding challenges, culminating in deep-dive technical discussions. The process is designed to test both your coding standards and your fundamental engineering instincts.

The journey begins with a standard recruiter screen, followed by a technical conversation with the hiring manager to assess your past projects and alignment with the team's goals. If you pass this stage, you will be given a take-home technical challenge with a set deadline (usually one week). Successful completion of this challenge leads to technical phone screens and a virtual onsite loop that focuses heavily on firmware architecture, protocol design, and hardware debugging.

The timeline above illustrates the typical progression from the initial application to the final decision. Candidates should use this roadmap to pace their preparation, ensuring they allocate ample time to complete the take-home challenge before moving into the intensive technical rounds. Note that response times between stages can vary, making persistent but polite follow-ups highly recommended.

To succeed at Brain, you must demonstrate mastery in several distinct technical domains. The interviewers will push you to explain the low-level mechanics of your implementations.

Serial Protocols & Packet Assembly

This is a heavily tested area. You must be comfortable writing code that handles asynchronous data streams, parses incoming bytes, and reconstructs packets reliably under real-time constraints.

Be ready to go over:

• Interrupt-driven I/O – Writing efficient Interrupt Service Routines (ISRs) that minimize execution time.
• Ring buffers – Implementing thread-safe circular buffers to decouple data reception from data processing.
• Framing and error checking – Using start/end bytes, escape characters, and CRCs to validate packet integrity.
• Advanced concepts (less common) – Implementing custom DMA descriptors for zero-copy packet processing and handling bus arbitration in multi-master configurations.

Example scenarios:

• "Design a state machine to parse a variable-length packet over UART where the transmitter may pause mid-packet."
• "Explain how you would recover from a framing error on a noisy serial bus without losing subsequent valid packets."

Hardware-Software Integration & Debugging

You must prove that you can move seamlessly between writing code and analyzing physical signals. Interviewers want to know how you diagnose issues when the software and hardware do not agree.

Be ready to go over:

• Logic analyzer utilization – Setting up triggers, capturing fast transients, and decoding protocol packets.
• Oscilloscope basics – Measuring rise times, detecting clock jitter, and diagnosing bus contention.
• Register-level debugging – Reading fault registers (e.g., HardFault handlers on ARM Cortex-M) to locate software crashes.

Example scenarios:

• "Your SPI sensor is returning all 0xFFs. Walk me through your step-by-step process using a logic analyzer to find the root cause."
• "How do you debug a system that randomly hangs once every few days?"

RTOS & Microcontroller Fundamentals

For roles working on BrainOS-enabled platforms, understanding real-time scheduling and resource constraints is critical.

Be ready to go over:

• Task scheduling – Preemptive vs. cooperative scheduling, task priorities, and rate-monotonic analysis.
• Concurrency primitives – Proper use of mutexes, semaphores, and queues without causing priority inversion.
• Memory management – Avoiding dynamic memory allocation (malloc) in safety-critical firmware to prevent heap fragmentation.

Example scenarios:

• "Explain a scenario where a low-priority task could block a high-priority task indefinitely, and how you would resolve it."
• "How do you calculate the stack size requirements for an RTOS task?"

As an Embedded Engineer at Brain, your daily tasks will revolve around developing, testing, and maintaining the firmware that drives autonomous robotic systems.

You will write clean, safety-critical C/C++ code for a variety of microcontrollers and processor architectures. This involves developing custom low-level drivers for hardware peripherals such as motor controllers, inertial measurement units (IMUs), LiDAR sensors, and battery management systems. You will work closely with hardware engineers during the prototyping phase to perform initial board bring-up, verifying that all components communicate correctly and that the hardware platform is stable.

Additionally, you will collaborate with the high-level software teams responsible for BrainOS. Your goal will be to ensure that the low-level controllers expose clean, reliable APIs to the robotic navigation stack. You will also participate in code reviews, write comprehensive unit tests, and design automated testing rigs to validate firmware releases before they are deployed to fleets of robots operating worldwide.