Staff Firmware Engineer, AI Native, Edge ML
Core
Build and own Life360's on-device ML platform, a reusable framework for running inference on resource-constrained edge devices (Tile trackers, Pet GPS) to process sensor data in real-time without draining battery or blowing memory budgets.
Role type
Staff Firmware Engineer (Edge ML Specialist)
Builds
On-device inference runtime, model integration pipelines, and sampling/preprocessing frameworks for Tile and Pet GPS trackers.
Domain
Consumer IoT / Edge AI / Embedded Systems
Deliverable
production ML models
Required skills
Embedded systems architecture, RTOS internals (Zephyr/FreeRTOS), driver development (SPI/I2C, DMA), power management, on-device model optimization (quantization), hardware debugging (JTAG, oscilloscope), AI-assisted tooling proficiency
Preferred skills
Experience training models for edge deployment, cross-layer firmware/hardware debugging, OTA model update management
Technologies
Zephyr, FreeRTOS, Cortex-M, SPI, I2C, JTAG, Logic Analyzers
Responsibilities
Architect and implement the on-device inference framework; integrate inference into resource-constrained RTOS firmware; debug cross-layer issues on real hardware; optimize models for extreme power/memory/latency constraints; drive alignment across firmware, app, cloud, and data science teams.
Seniority
Staff, hands-on IC with technical direction
