Software Development Engineer - Location Technologies, Sensing & Connectivity

What you'll do

• Design and implement location state estimation algorithms that fuse multi-modal sensor data like GPS, WiFi, and IMU.
• Develop on-device machine learning models for place inference and behavioral forecasting within strict power and memory constraints.
• Build clustering and pattern recognition algorithms to identify significant locations and routes from noisy sensor data.
• Create and optimize data processing pipelines that operate efficiently on mobile hardware at a massive scale.
• Collect, curate, and analyze real-world datasets to train models and validate algorithm performance.
• Integrate production-ready code in Objective-C, Swift, or C++ into system frameworks and daemons.
• Profile and optimize system performance metrics including CPU usage, memory footprint, and battery consumption.

What we're looking for

• 5+ years of experience developing commercial software, preferably systems-level or embedded software on resource-constrained devices.
• Strong programming skills in C, C++, Objective-C, or Swift with a solid foundation in algorithms and data structures.
• Working knowledge of statistics and probability, including histograms, probability distributions, Bayesian inference, and hypothesis testing.
• Experience evaluating and optimizing system performance regarding memory footprint, CPU usage, power consumption, and I/O.
• Deep expertise in location technologies such as GPS/GNSS, WiFi-based localization, indoor positioning, and sensor fusion (preferred).
• Experience with machine learning for time-series data, spatial data, or behavioral prediction, including on-device ML optimization (preferred).
• Background in signal processing, Kalman filtering, particle filters, or other probabilistic state estimation techniques (preferred).
• Experience with clustering algorithms and unsupervised learning applied to spatial or temporal data (preferred).