Senior Machine Learning Engineer II

• 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