Location Estimation Engineer, Sensing & Connectivity

Develop and improve multi-sensor navigation technology as a location estimation engineer. Craft the next generation of location-aware mobile experiences by working on state-of-the-art technologies to seamlessly integrate people's digital and physical lives. Are you passionate about building technology that will make a difference? Do you flourish with good creative challenges? Do you love attention to detail? If so, we might just be the team for you.\\n

Here at Apple, we build devices and services that enrich our customers' lives. In the location technologies group, we help people connect: with each other, and with our planet. We reach more than a billion people. We help them find their way, and we help them find each other. We help them stay healthy, and sometimes we even save their lives. What we do and how we do it makes a difference. Join our team, and we'll help you do the best work of your life.\n\nIf you join our team, you'll research, design, develop, debug, and support location estimation software. You'll also collaborate to qualify performance and support commercialization for hundreds of millions of users on multiple hardware families. You'll work with customers of location, both internal and external, to make best use of your work to support their applications.

Graduate degree in Engineering, Computer Science or a related field or a Bachelor's degree with equivalent experience in positioning and Bayesian estimation.\nProficient in Bayesian estimation concepts and Kalman filtering\nProficient in statistics concepts and statistical data analysis\nProficient in C++\nFamiliar with modern object-oriented programming concepts and design patterns\n

Interested in location technologies and eager to experiment with state-of-the-art techniques\nGood collaborator and communicator\nProficient in GPS / GNSS / radionavigation theory and technology\nExperience with inertial navigation systems, visual localization, or other positioning techniques\nFamiliarity with machine learning\nComfortable implementing complex mathematical algorithms