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Job Description
📋 Description Own on-device ML platform: design, implement, and ship reusable inference framework for Life360 Firmware ownership: integrate ML into RTOS firmware (Zephyr/FreeRTOS) with drivers, power, and Develop and ship models on device: quantization, operator support, latency/memory tradeoffs within Optimize for extreme resource constraints: balance model accuracy, power, and footprint in Set direction across firmware, app/cloud, data science, hardware, and ops; raise embedded-ML Lead AI-native development practices; mentor teammates and define what AI-native means for embedded 🎯 Requirements 10+ years firmware engineering; track record shipping at scale from prototype to mass production. Bachelor's degree in Electrical Engineering, Computer Science, or related field. Deep C/C++ for embedded systems; fluent in RTOS internals (Zephyr, FreeRTOS, or equivalent). Low-level hardware skills: SPI/I2C/UART, DMA, interrupts; strong debugging (scope, logic analyzer Experience deploying ML models on microcontroller-class hardware in a shipping product; on-device Hands-on with embedded inference frameworks (TFLite Micro, CMSIS-NN, ExecuTorch, or equivalent) and 🎁 Benefits Competitive pay and benefits; medical/dental/vision/LTD plans; plans for Canadian employees as 401(k)US with company match; RRSP/DPSP for Canadian employees. Employee Assistance Program; Flexible PTO and company-wide days off. Remote-friendly equipment/tools reimbursement; paid Life360 Platinum membership and Tile products. Learning & Development programs; multiple life-cycle benefits and wellness support.
