Senior Machine Learning Engineer II at Life360

Prince Rupert, British Columbia, Canada -

Full Time

Start Date

Immediate

Expiry Date

27 Dec, 25

Salary

228000.0

Posted On

28 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, Java, Model Development, ML Ops, APIs, Data Pipelines, Experiment Design, Microservices, Containerization, AWS, DynamoDB, Kubernetes, Recommendation Systems, Mobile Applications, Kafka

Industry

Individual and Family Services

Description

About Life360 Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app and Tile tracking devices empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 88 million monthly active users (MAU), as of June 2025 across more than 180 countries. Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends that basically are family). Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com. Life360 is a Remote First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US) regardless of any specified location above. About the Job The newly formed AI Growth Enablement team sits at the intersection of Product, Data Science, and Engineering. Our charter is to unlock step-function growth in users, subscribers, and revenue by building shared AI/ML capabilities — including but not limited to experimentation and automation tools, generative AI models, predictive-model APIs, and self-serve tooling—that accelerate decision-making, experimentation and automation across multiple product teams. You’ll partner closely with Data Scientists and other Cloud engineers in the Growth organization, as well as Data Analysis teams and mobile enigneers, to turn data and models into delightful, effective experiences at scale, and to empower each team to leverage AI/ML in the most effective way to drive user and revenue growth. Come join us as we build the infrastructure to handle our ever growing user base. We will continue to break down our monolith in favor of microservices that service our mobile clients today. You will be working alongside our Architecture and Product teams to move fast as we expand the business to build a recommendation engine that empowers rapid experimentation. Together, we will build systems that are strong and reliable to uphold a heavy load, yet malleable to fit many product demands. For candidates based in the US, the salary range for this position is $155,000 to $228,000 USD. For candidates based out of Canada, the salary range for this position is $176,000 to $206,000 CAD. We take into consideration an individual's background and experience in determining final salary- therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity. What You’ll Do 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 Staff engineers Handle on call rotation and address live incidents What We’re Looking For 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 - 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) We value having a diverse and inclusive community from many backgrounds, so even if you don’t meet 100% of the above qualifications, you should still seriously consider applying! Our Benefits 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 Life360 Values Our company’s mission driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference Be a Good Person - We have a team of high integrity people you can trust. Be Direct With Respect - We communicate directly, even when it’s hard. Members Before Metrics - We focus on building an exceptional experience for families. High Intensity, High Impact - We do whatever it takes to get the job done. Our Commitment to Diversity We believe that different ideas, perspectives and backgrounds create a stronger and more creative work environment that delivers better results. Together, we continue to build an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. It fuels our innovation and connects us closer to our customers and the communities we serve. We strive to create a workplace that reflects the communities we serve and where everyone feels empowered to bring their authentic best selves to work. We are an equal opportunity employer and value diversity at Life360. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any legally protected status. We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful. #LI-Remote

Responsibilities

You will partner with Product, Data Science, and Cloud Engineering to design and deploy ML models that power personalization, experimentation, and automation use cases. Additionally, you will build, productionize, and maintain real-time model APIs for recommendations and predictive targeting.