Staff Firmware Engineer, AI Native, Edge ML

Role Description

We're looking for a Staff Firmware Engineer to build and own Life360's on-device ML platform — the reusable framework that lets any device in our portfolio sample sensor data, run inference on the edge, and act on it without draining the battery or blowing the memory budget.

• You are a firmware engineer first — deeply fluent in embedded systems and on-device software, from RTOS internals and driver bring-up to power management and debugging on real hardware.
• You are an Edge ML specialist second — you know how to get a model running, quantized and optimized, on a Cortex-M-class part with kilobytes to spare.
• "Staff" here means you set the technical direction for on-device ML and you ship it — you architect the platform and write the code that proves it works.
• This is a foundational role. You'll turn the first feature into the foundation the rest of the portfolio builds on, with a lot of room to grow from there.

Qualifications

• 10+ years of firmware engineering, taking complex consumer hardware from prototype through mass production.
• Bachelor's degree in Electrical Engineering, Computer Science, or a related field.
• Deep C/C++ for embedded systems and real fluency in RTOS internals (Zephyr, FreeRTOS, or equivalent).
• Strong low-level hardware skills — SPI/I²C/UART, DMA, interrupts, driver development from the datasheet up.
• Demonstrated experience deploying ML models on microcontroller-class hardware in a shipping product.
• Hands-on with embedded inference frameworks (TFLite Micro, CMSIS-NN, ExecuTorch, or equivalent).
• Solid grounding in the sensor data and signal-processing pipelines that feed a model (IMU and similar).

Requirements

• Integrate inference into resource-constrained RTOS firmware (Zephyr / FreeRTOS) without compromising stability, scheduling, or power.
• Debug on real hardware (oscilloscope, logic analyzer, JTAG) and drive cross-layer issues to root cause across the firmware/hardware boundary.
• Get models running within firmware constraints — handling quantization, operator support, and the latency/memory tradeoffs.
• Squeeze inference into tight power, memory, and latency envelopes, and own the tradeoffs between model accuracy, power draw, and footprint.
• Drive alignment across firmware, app/cloud, data science, hardware, and ops on how on-device intelligence gets built.

Benefits

• Competitive pay and benefits.
• Medical, dental, vision, life and disability insurance plans (100% paid for US employees).
• 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.
• Employee Assistance Program (EAP) for mental wellness.
• Flexible PTO and 12 company-wide days off throughout the year.
• Winter and Summer Weeklong Synchronized Company Shutdowns.
• Learning & Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership for your preferred circle.
• Free Tile Products.