Location Estimation Scientist, Sensing u0026 Connectivity

Build the systems and algorithms that power location intelligence for billions of people. Craft the next generation of location-aware experiences by combining strong software engineering, machine learning, signal processing, and data infrastructure to seamlessly connect people's digital and physical lives - at a scale few engineers ever get to work with. Are you passionate about writing clean, scalable code and applying ML to real-world sensor problems in clever ways? Do you love digging into data, building intelligent systems, and proposing bold ideas - not just implementing them? Do you want your work to have real impact - from someone's daily commute to a life-critical emergency? If so, we might just be the team for you.Here at Apple, we build devices and services that enrich our customers' lives. In the location technologies group, we power navigation, emergency response, fitness, and a rapidly expanding set of indoor and outdoor services across new and existing hardware - spanning the full stack from raw sensors to the application layer. We reach more than a billion people every day, and what we do makes a difference. Join our team, and we'll help you do the best work of your life.Demonstrated experience designing signal processing or sensor fusion algorithms in production environments Demonstrated experience applying ML to sensor data challenges such as classification, regression, anomaly detection, or signal modeling Experience building and maintaining large-scale data pipelines handling crowdsourced, sensor, or telemetry data Proficient in Python, Java, or equivalent languages suitable for ML, algorithm, and infrastructure development Strong communication skills - you can explain complex systems and algorithmic ideas clearly to any audience Curious and energized by problems that do not have obvious solutions yetStrong foundation in signal processing theory and its practical application to real-world sensor systems Hands-on experience with machine learning - including model development, training, evaluation, and production deployment Strong software engineering fundamentals - writing clean, maintainable, and well-tested code in production environments Master's or PhD in Electrical Engineering, Computer Science, Machine Learning, or related field, or a Bachelor's degree with demonstrated experience shipping production systems