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Senior Machine Learning Engineer II at Life360. Location Information: United States. Life360 brings families closer with smart tools designed to protect and connect the people who matter most.. Partner with Product, Data Science, and Cloud Engineering to design and deploy ML models that power personalization, experimentation, and automation use cases. Build, productionize, and maintain real-time model APIs for recommendations, predictive targeting, and generative AI experiences. Work with backend and mobile engineers to integrate model outputs directly into user-facing features. Contribute to the development of self-serve ML infrastructure to accelerate experimentation across product teams. Design and implement feature pipelines, model training workflows, and scalable inference systems. Collaborate on our long-term vision for a flexible, extensible ML platform that supports multiple use cases across Growth and Core product teams. Monitor and maintain model health, performance, and drift in production. Build the recommendation engine that helps Life360 surface the most relevant feature or plan to the right user at the right time. Deploy an ML model to predict the optimal moment to nudge a user to subscribe to Premium. Create infrastructure for personalized notifications that adapt in real time to user behavior. Monitor health, suggest improvements for and deploy your own services. Mentor other developers who are trying to grow. Build technical specs with Staff engineers. Handle on call rotation and address live incidents. Bachelor’s degree in Computer Science, Machine Learning, Applied Math, or a similar quantitative field—or equivalent industry experience. 5+ years of professional experience in building and deploying ML models in production. Strong proficiency in Python or Java, model development libraries (e.g. PyTorch, TensorFlow, scikit-learn), and ML Ops tools. Experience with serving ML models behind scalable APIs with low-latency performance requirements. Ability to design, build, and manage real-time and batch data pipelines, ideally in collaboration with Data Engineering. Knowledge of experiment design, A/B testing, and causal inference methods for ML product validation. Familiarity with microservices architecture, containerization (Docker, Kubernetes), and modern deployment pipelines. Comfortable collaborating cross-functionally with mobile, backend, and data platform teams. Experience building recommendation systems or ranking models. Experience integrating models into mobile client applications. Familiarity with streaming systems like Kafka. Experience working with Kafka Streams. Experience with AWS (EC2, EKS, DynamoDB, Kinesis), databases (MySql), Languages (Java, Python, PHP). Pay range:. $155K - $228K. Competitive pay and benefits. Medical, dental, vision, life and disability insurance plans (100% paid for employees). 401(k) plan with company matching program. Employee Assistance Program (EAP) for mental wellness. Flexible PTO and 12 company wide days off throughout the year. Learning & Development programs. Equipment, tools, and reimbursement support for a productive remote environment. Free Life360 Platinum Membership for your preferred circle