Staff Machine Learning Engineer, Revenue
Life360
full-time
Posted on:
Location Type: Remote
Location: Remote • California • 🇺🇸 United States
Visit company websiteSalary
💰 $175,500 - $258,500 per year
Job Level
Lead
Tech Stack
AWSCloudDockerDynamoDBEC2JavaKafkaKubernetesMicroservicesMySQLPHPPythonPyTorchScikit-LearnSQLTensorflow
About the role
- 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
- Example: Build the recommendation engine that helps Life360 surface the most relevant feature or plan to the right user at the right time
- Example: Deploy an ML model to predict the optimal moment to nudge a user to subscribe to Premium
- Example: 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 other Staff engineers
- Handle on call rotation and address live incidents
Requirements
- Bachelor’s degree in Computer Science, Machine Learning, Applied Math, or a similar quantitative field—or equivalent industry experience
- 8+ years of experience building and shipping ML-powered systems
- Strong proficiency in Python or Java, model development libraries (e.g. PyTorch, TensorFlow, scikit-learn), SQL, 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 - bonus if you have experience with StatSig
- Familiarity with microservices architecture, containerization (Docker, Kubernetes), and modern deployment pipelines
- Comfortable collaborating cross-functionally with mobile, backend, and data platform teams
- Bonus: Experience building recommendation systems or ranking models
- Bonus: Experience integrating models into mobile client applications
- Bonus: Familiarity with streaming systems like Kafka
- Bonus for experience working with Kafka Streams
- At Life360 we use certain technologies, experience with these technologies will serve you well: AWS (EC2, EKS, DynamoDB, Kinesis), databases (MySql), Languages (Java, Python, PHP)
Benefits
- Competitive pay and benefits
- Medical, dental, vision, life and disability insurance plans (100% paid for employees)
- 401(k) plan with company matching program
- Mental Wellness Program & Employee Assistance Program (EAP) for mental well being
- Flexible PTO, 13 company wide days off throughout the year
- Winter and Summer Week-long 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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonJavaPyTorchTensorFlowscikit-learnSQLML Opsreal-time data pipelinesbatch data pipelinesA/B testing
Soft skills
collaborationmentoringcommunicationproblem-solvingcross-functional teamwork