Jobs at Life360

Partner with web product, marketing, engineering, and finance teams to own web analytics strategy and drive actionable decisions. Design and evaluate experiments and causal analyses, define metrics, ensure event instrumentation, and translate findings into product and growth recommendations. Use SQL and Python/R for statistical analysis, deploy experimentation platforms, and help shape AI-native analytics automation. Focus is on measurement, causality, and moving teams to act—not production ML.

Build and operate high-throughput experimentation and recommendation infrastructure. Design APIs and services, use agentic AI workflows (LLMs) for development, ensure performance and reliability, participate in on-call, mentor teammates, and codify AI-native engineering practices.

Lead strategy and execution to grow Life360 subscriptions by defining membership architecture, pricing and packaging, partner monetization, freemium feature roadmaps, experimentation, and AI-native product practices. Drive revenue-per-member, partner integrations, and cross-functional delivery while advocating subscriber value and satisfaction.

Lead product and strategy operations for a large engineering department: own OKR/QBR cycles, roadmaps, weekly execution alignment, centralize artifacts, transform workflows to AI-native, coordinate cross-functional intake, flag risks, and drive high-priority cross-functional projects from inception to launch.

Design, implement, and own a reusable on-device ML inference platform for resource-constrained devices. Integrate inference into RTOS firmware, develop drivers and DMA paths, debug on real hardware, train and optimize models for microcontroller-class hardware, and ship features to production while raising team expertise and using AI-assisted tooling.

Lead architecture and implementation of high-throughput, low-latency AdServer and Exchange services. Design scalable, resilient distributed systems, integrate demand/supply partners, improve RTB/auction capabilities, advance observability and automation (including AI-driven testing/IaC), and mentor engineers to increase platform reliability and revenue growth.

Design, build, and maintain scalable dbt transformation pipelines and dimensional data models on Databricks. Partner with data engineering and stakeholders to deliver trusted silver/gold datasets, implement data quality tests and monitoring, enable self-service semantic layers, and enhance LLM-driven tooling to accelerate analytics and automation.

Embed with product, engineering, marketing, and finance teams to own analytical narratives, establish causality via experimentation and causal inference, define measurement strategies, drive actionable insights, shape AI-native analytics tooling, and mentor senior analysts. Focus is on decisions and measurable impact rather than dashboards.

Partner with product, engineering, marketing, and finance to drive decisions using causal inference, experimentation, and analytics. Own measurement strategy, present actionable insights, shape AI-native analytics tooling, and ensure analyses translate into product and business outcomes.

Own analysis and algorithmic solutions for ads delivery; train, deploy, and scale ML/optimization models into production; build logging, monitoring, and lineage; improve data pipelines; mentor data scientists; use agentic AI tools daily; collaborate with engineers to integrate models into ads systems and handle on-call production incidents.

Design, build, and scale MLOps infrastructure and CI/CD/continuous training pipelines. Deploy and monitor ML models as microservices or batch jobs, manage cloud GPU/CPU resources with IaC, enable observability for model drift and latency, and collaborate with data scientists, engineers, and product teams to ensure reproducibility, compliance, and production reliability.

Lead Life360's Data Engineering organization and own end-to-end data platform and analytics engineering strategy. Define architecture for ingestion, transformation, modeling, and serving data for humans and LLMs. Manage engineering managers and teams, drive self-serve data capabilities, cost management, vendor decisions, data quality/governance, and partner cross-functionally to prioritize engineering work that drives business impact.

Lead global DTC eCommerce strategy and web experience to drive revenue, conversion, and LTV. Own site roadmap, experimentation and personalization programs, analytics-driven optimization, cross-functional alignment, vendor/tech requirements, and commercial plans to scale global digital sales and improve customer journeys.