Firmware Engineer

Firmware Engineer (Consumer Health Robotics)Location: Austin, TX (South Congress)Setting: 100% On-site (5 days/week)Compensation: $145,000 – $175,000 + EquityTHE MISSIONThey are building a first-of-its-kind wearable for the home that tracks gut health andhydration through multispectral imaging. The team is on a mission to make internal health tracking as seamless as sleep tracking, ultimately aiming to provide early detection for chronic conditions.THE ROLEThe company is looking for a Firmware Engineer to take full ownership of the devicefirmware stack. Replacing an overseas contractor, this individual will be the sole owner ofthe firmware lifecycle in the Austin office. This is a "hands-on-hardware" role requiringsomeone who can physically debug boards, iterate on sensors, and ensure 99.9%reliability for a connected consumer device.WHAT YOU’LL DOFull Stack Ownership: Own the entire firmware stack end-to-end—from initialhardware bring-up to fleet management.Power Optimization: Be "maniacal" about millisecond-level power draw to hit anambitious 60-day battery life target.Sensor Stability: Debug and stabilize noisy sensors (presence detection, thermal/heater control) to maximize performance.Mission-Critical Updates: Build and maintain robust OTA update systems where reliability is paramount to prevent device bricking.Cross-Functional Collaboration: Work closely with the co-founding team to bridge hardware, cloud telemetry, and product UX.QUALIFICATIONSShipping Experience: 4+ years of experience shipping production-grade firmware forconnected consumer hardware.Technical Stack: Expert-level C, MCU, and RTOS experience. Specific experience withRealtek (Ameba Pro 2) or BLE is a major plus.Debugging Skills: Proven ability to use logic analyzers and oscilloscopes to solvehardware-level timing and noise issues.Ownership Mindset: Excited to move from a "contractor" model to a "foundingengineer" model with high autonomy and visibility.TECHNICAL STACKC RTOS Realtek Ameba Pro 2 BLE OTA Infrastructure Ultra-Low Power Optimization