Leverage a dataset consisting of hundreds of millions of user actions a day to model, analyze and predict user behavior to not only create incredible gameplay experiences but help people change their lives with games based in the real world.
PhD in Computer Science with a thesis in machine learning, or thesis grounded in machine learning techniques in other engineering or science fields.
Repeated experience analyzing and creating empirically verifiable models based on real-world data using multiple approaches.
Join the Niantic team!
Niantic’s mission is to use emerging technology to create experiences in the real world. We build products that inspire outdoor exploration, exercise, and face-to-face social interaction.
Originally formed at Google in 2010, we became an independent company with a strong group of investors including Nintendo, The Pokémon Company, and Alsop Louie Partners. We build games that get people outside and exploring. We enable our players to have fun while visiting new places, learning about the world around them, and meeting new friends.
We launched Ingress, an immersive real-world mobile game played by millions of people in over 200 countries and territories, and downloaded over 20 million times. We also develop Pokémon GO, which has broken world records and been downloaded over 750 million times in its first year. We announced Harry Potter: Wizards Unite, our latest much-anticipated AR game.
We're a hard-working, fun, and exciting group who love what we do! We have offices located in San Francisco, Sunnyvale, Bellevue, Los Angeles, Tokyo, and Hamburg.
About Niantic inc.
Leaders in Augmented Reality
Niantic is building a state of the art augmented reality platform for current and future generations of AR hardware.
Our real-world gaming platform includes a massively scalable engine for shared state and user interactions already proven to support hundreds of millions of users and a client platform that sets the standard for mapping, security, and AR capabilities.
Niantic is hard at work solving challenges to realize the full potential of augmented reality using technologies such as machine learning and computer vision.