AI Embedded Systems Engineer
Role details
Job location
Tech stack
Job description
We are hiring an AI Embedded Engineer to own critical firmware on our system, a dense board full of peripherals, motion control, fluid handling, and a reliability target measured by the fact that real people will take real medical action based on what your code outputs. This is not a role for someone who wants to stay inside the firmware box. This is a tightly coupled electro-mechanical-optical-fluidic-biochemical system. The best engineer on this team is the one who can step out of their editor, walk over to the bench, put a scope on a rail, talk to the optics lead about why a signal is drifting, and come back with the right firmware fix - not the convenient one. You will work across the main system MCU and a constellation of peripheral micros. You will write production firmware, design bring-up flows, debug timing and control loops at the processor level, and own reliability. You will also be one of the people pushing hard on what AI can do for embedded development at SiPhox and what AI can do on the device itself., * Own firmware. STM32 + RTOS, HALs, real-time state machines, event-driven control, inter-module comms. Production code that has to work every time.
- Work across peripheral micros. BLDC motor controller firmware, reader micro, sensor controllers. Define the protocols and timing budgets between them.
- Deliver bring-up through V&V to commercial release. Integrating across sensors, motion, fluidics, photonics, app, and cloud.
- Debug across disciplines. Put a scope on a board. Read a fluidic schematic. Ask the mech team a sharp question. Find the actual root cause, not the most convenient one.
- Own reliability and safety behaviors. Hazard analysis inputs, FMEA, fault-tolerant designs, bootloaders, calibration flows, diagnostics, watchdogs that actually catch things.
- Build verification automation. Test fixtures, HIL setups, traceability - the boring infrastructure that lets the team move fast without lying to itself.
- Push AI deeper into how we build. And into what the device itself can do.
- Contribute to the Design History File. We are a medical device. The details matter.
Requirements
BS in EE, CE, CS, or equivalent. US work authorization. Occasional travel., * Strong C/C++ for embedded - drivers, bring-up, real-time control, the actual register-level stuff.
- Solid RTOS experience (FreeRTOS, Zephyr, ThreadX, or similar.
- STM32 or comparable Cortex-M experience, and comfort moving between MCU families.
- Motion or electromechanical control: steppers, servos, BLDC, closed-loop control.
- Firmware architecture ownership on a real product - not just contributions to someone else's.
- Excellent cross-disciplinary debugging instincts - you can find the bug even when it isn't yours.
- Active, fluent use of AI coding tools, and the fundamentals to verify what they produce.
- A quality bar that does not bend under deadline pressure - you would be happy for your mother to be the patient on the other end of your code.
- Top-tier work ethic, ownership mindset, and a low-ego working style.
Preferred Skills
- Shipped complex electromechanical products end-to-end.
- Hands-on with on-device ML: quantization, TFLite Micro, CMSIS-NN, or equivalent.
- Fluidics, liquid handling, or lab automation.
- Optical or photonic systems experience.
- Bootloaders, OTA updates, cybersecurity (524B, SBOM, threat modeling.
- CI/CD and test automation in regulated environments.
- Medical device firmware experience (IEC 62304 Class B or C, ISO 13485, ISO 14971).
Benefits & conditions
Pay range and compensation package
Competitive salary and significant equity. Healthcare, dental, 401k. Two company-wide shutdown weeks (July and December) on top of PTO. High-end gym membership. Relocation support available.
Equal Opportunity Statements
SiPhox is committed to diversity and inclusivity in the workplace.
A Few Questions We Will Ask
- Walk us through a firmware bug you found that nobody else on the team would have found. What made you the one who found it?
- How are you using AI in your embedded workflow today? Where does it help, and where does it actively hurt?
- Tell us about a time you had to make a tradeoff between shipping and correctness in safety-critical code.
- What did you do? If we asked you to run inference on an STM32, where would you start?