Staff Firmware Engineer, AI Native, Edge ML
About The Position
Life360 is seeking a Staff Firmware Engineer with expertise in AI Native and Edge ML to join their Connected Devices team. This role is responsible for building and owning the on-device ML platform, a reusable framework that enables devices to sample sensor data, run inference at the edge, and act on it efficiently. The ideal candidate is a firmware engineer first, deeply skilled in embedded systems, RTOS, driver bring-up, and power management, and an Edge ML specialist second, capable of optimizing and deploying ML models on resource-constrained microcontrollers. This is a foundational role with significant impact, requiring the ability to set technical direction, architect the platform, write code, and debug production issues. The engineer will also contribute to regular firmware tasks when ML demand is light, ensuring a well-rounded contribution to the team. Success in the first year involves owning the on-device ML domain end-to-end, shipping the platform to the fleet, resolving production issues, and contributing to 2-3 on-device ML features for the Pet GPS fleet. The role emphasizes an AI-Native approach, using AI tools as a development partner across firmware and ML tasks, and raising the team's overall AI fluency.
Requirements
- 10+ years of firmware engineering experience, taking complex consumer hardware from prototype through mass production, with a demonstrated track record of shipping at scale.
- Bachelor's degree in Electrical Engineering, Computer Science, or a related field.
- Deep C/C++ expertise for embedded systems and fluency in RTOS internals (Zephyr, FreeRTOS, or equivalent).
- Strong low-level hardware skills (SPI/I²C/UART, DMA, interrupts, driver development) and hands-on debugging experience (scope, logic analyzer, JTAG).
- Demonstrated experience deploying ML models on microcontroller-class hardware in a shipping product.
- Hands-on experience with embedded inference frameworks (TFLite Micro, CMSIS-NN, ExecuTorch, or equivalent) and model optimization (quantization, pruning).
- Ability to develop and train ML models, not just deploy existing ones.
- Solid grounding in sensor data and signal-processing pipelines (IMU and similar).
- Experience using AI coding tools (Claude Code or equivalent) as a development partner.
- Strong written communication skills and a habit of documenting decisions.
- Ability to work across firmware, hardware, and data science teams.
Nice To Haves
- Security and compliance for connected devices (secure boot, key provisioning, signed OTA, RF/regulatory certification).
- Hands-on experience with cellular, BLE, GPS/GNSS, or audio subsystems on battery-powered wearables or trackers.
- New-board bring-up experience (powering up hardware, verifying peripherals, initial firmware).
- Hardware schematic evaluation and partnership with EE on design reviews.
- Factory and manufacturing support experience (test development, production-line bring-up, yield/quality support).
Responsibilities
- Build and own the on-device ML platform, including the runtime, model integration path, and sampling/preprocessing pipeline.
- Design and implement the platform-level calls for runtime, model format, memory/flash budgeting, and OTA model updates.
- Own the end-to-end lifecycle of the platform: architecting, implementing, and debugging field issues.
- Integrate inference into resource-constrained RTOS firmware (Zephyr/FreeRTOS) without compromising stability, scheduling, or power.
- Own low-level firmware plumbing, including drivers, DMA data paths, SPI/I²C, and middleware.
- Debug on real hardware using tools like oscilloscopes and logic analyzers, and resolve cross-layer issues.
- Perform regular firmware engineering tasks, including features, bug fixes, field issue resolution, and on-call duties, when ML demand is light.
- Develop and ship ML models on device, handling quantization, operator support, and latency/memory tradeoffs.
- Optimize inference for tight power, memory, and latency constraints, balancing model accuracy, power draw, and footprint.
- Drive alignment across firmware, app/cloud, data science, hardware, and operations teams on on-device intelligence development.
- Raise the team's embedded-ML fluency through code reviews, design documents, and pairing.
- Utilize AI tooling as a development partner for firmware and ML tasks, and help define AI-native practices for embedded work.
Benefits
- Competitive pay and benefits.
- Medical, dental, vision, life and disability insurance plans (100% paid for US employees).
- Supplemental medical and dental plans for Canadian employees.
- 401(k) plan with company matching program in the US.
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
