Life360

Life360

Staff Firmware Engineer, AI Native

Remote, USA; Remote, Canada · Staff+

Sponsorship not specified$143k-$262kDetected 15 days ago
C++CRailsCode ReviewRESTMachine LearningData AnalysisData ScienceBudgetingEmbedded SystemsElectrical EngineeringSensorsLeadershipCommunication

Stay score

odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

Personalize to your clock →

Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

7 transfer filings in the last year, covering 7 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

No reports yet — be the first to help the next applicant.

About the role

  • We're an AI-Native engineering team: AI isn't just a tool we use, it's how we work - across specifications, code, test, review, data analysis and triage.
  • Today that means firmware running across our Tile and Pet GPS tracker lines - devices shipping in the hundreds of thousands of units, each streaming continuous multi-sensor telemetry - which is the scale this on-device ML platform should be built to handle.
  • This role reports to the Engineering Manager, Connected Devices, and works day-to-day alongside our firmware, app, and cloud engineers, data science, hardware, operations, and data teams.

Responsibilities

  • Build and Own the On-Device ML Platform
  • Design and build the reusable on-device inference framework any Life360 device can adopt - the runtime, the model integration path, and the sampling and preprocessing pipeline - and make the platform-level calls (runtime and model format, memory/flash budgeting, OTA model updates).
  • Own it end to end: you architect it, implement it, and debug it when it misbehaves on a device in the field.
  • Integrate inference into resource-constrained RTOS firmware (Zephyr / FreeRTOS) without compromising stability, scheduling, or power, and own the low-level plumbing - drivers, DMA data paths, SPI/I²C, and the middleware that feeds the pipeline.
  • Debug on real hardware (oscilloscope, logic analyzer, JTAG) and drive cross-layer issues to root cause across the firmware/hardware boundary.
  • Develop and Ship Models on Device
  • Get models running within firmware constraints - from Data Science or built and trained yourself, increasingly with AI-assisted tooling - handling quantization, operator support, and the latency/memory tradeoffs.
  • Own the whole loop, from training output to validated on-device behavior. You don't take a model over the wall and hope.
  • Optimize for Extreme Constraints
  • Squeeze inference into tight power, memory, and latency envelopes, and own the tradeoffs between model accuracy, power draw, and footprint - validated in the real world, not just on the bench.

Requirements

  • 10+ years of firmware engineering, 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.
  • Demonstrated experience deploying ML models on microcontroller-class hardware in a shipping product - not a course project or one-off PoC.

Nice to have

  • Security and compliance for connected devices - secure boot, key provisioning, signed and rollback-safe OTA, and RF/regulatory certification (FCC/CE).
  • Hands-on experience with cellular, BLE, GPS/GNSS, or audio subsystems on battery-powered wearables or trackers.
  • New-board bring-up - powering up unproven hardware, verifying power rails and peripherals, and getting first firmware running on a fresh board.
  • AI-Native Expectations
  • This isn't autocomplete
  • Judgment and ownership - you review every line of AI-generated code and every AI-assisted model output as critically as you would a human PR before it ships to a device in the field.
  • The AI writes it
  • you're accountable for it.

Compensation

  • For candidates based in the US, the salary range for this position is $143,000 to $261,500 USD.

Company info

  • The Connected Devices team at Life360 owns end-to-end device software readiness across our portfolio - firmware, app, and cloud engineering working as one team to ship the trackers and wearables that keep families connected to the people, pets, and things they care about most.
Apply directly at Life360 →Create a free account for alerts like thisView Life360 immigration profile

This listing is sourced directly from Life360's careers page and normalized into a canonical job model.