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.

Description

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.

If 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.

Minimum Qualifications

Graduate degree in Engineering, Computer Science or a related field or a Bachelor's degree with equivalent experience in positioning and Bayesian estimation.

Proficient in Bayesian estimation concepts and Kalman filtering

Proficient in statistics concepts and statistical data analysis

Proficient in C++

Familiar with modern object-oriented programming concepts and design patterns

Preferred Qualifications

Interested in location technologies and eager to experiment with state-of-the-art techniques

Good collaborator and communicator

Proficient in GPS / GNSS / radionavigation theory and technology

Experience with inertial navigation systems, visual localization, or other positioning techniques

Familiarity with machine learning

Comfortable implementing complex mathematical algorithms