Machine Learning Engineer

About Life
360

Life
360’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. Life
360 serves approximately 88 million monthly active users (MAU), as of June 2025 across more than 180 countries.

Life
360 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).

Life
360 has more than 500 (and growing!) remote-first employees. For more information, please visit

Life
360 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 and Canada) regardless of any specified location above.

The Location Platform team supports our mission to deliver peace of mind and make everyday family life better through a best-in-class app—uniquely powered by fast, insightful, and delightful location-forward experiences that drive lasting loyalty and ongoing engagement.

We build and maintain a robust foundation that enables us to rapidly deliver exceptional value, quality, and delight to our members. This includes the precise collection and delivery of location and sensor data from member devices, powering the direct app experience and the development of innovative products across Life
360. We obsess over performance—continuously measuring and improving key metrics to ensure a reliable, seamless, and scalable platform for our 80M+ global members.

At Life
360, location isn’t just a feature – it’s the foundation. As a Staff Machine Learning Engineer on the Location Platform team, you’ll architect the intelligence layer behind that foundation. Your work will directly influence core experiences around location alerting, sharing, and mobility – each playing a critical role in how users understand, trust, and engage with our platform.

This is a hands-on technical role. You’ll collaborate closely with our Director of Location Engineering and act as a key contributor in realizing the long-term strategic vision of a location platform that is intelligent, adaptive, and always a step ahead.

For candidates based in the US, the salary range for this position is $175,500 to $258,500 USD. For candidates based out of Canada, the salary range for this position is $197,500 to $233,500 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.

• Design and lead end-to-end ML systems that enhance our understanding of real-world movement and context, including destination inference, anomaly detection, and modality prediction.
• Partner with Data Science to translate advanced modeling research into scalable production systems. Define instrumentation, evaluate performance, and guide experimentation.
• Build and maintain ML pipelines, from signal ingestion and feature engineering through training, deployment, and real-time inference at scale.
• Integrate ML into user-facing features, ensuring that intelligence translates into clarity, safety, and trust within our mobile experience.
• Champion operational excellence, owning system health through model monitoring, drift detection, and continuous improvement loops.
• Contribute to architectural strategy alongside engineering leadership, ensuring our ML systems are extensible, maintainable, and aligned with long-term platform vision.
• Mentor and multiply—help elevate the ML and engineering craft across the broader Location team.