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 handle large volumes of location events while preserving user privacy.
• Integrate complex algorithms into production code using Objective-C, Swift, or C++ for high-scale deployment.
• Profile and optimize system performance metrics including CPU usage, memory footprint, and battery consumption.
• Collect and analyze real-world datasets to train models and validate algorithm performance across diverse populations.

What we're looking for

• 5+ years of experience developing commercial software, preferably systems-level or embedded software for resource-constrained devices.
• Proficiency in C, C++, Objective-C, or Swift with a strong foundation in algorithms and data structures.
• Working knowledge of statistics and probability, including Bayesian inference and hypothesis testing.
• Experience evaluating and optimizing system performance metrics such as memory footprint, CPU usage, power consumption, and I/O.
• Expertise in location technologies including GPS/GNSS positioning, WiFi localization, and sensor fusion for state estimation.
• Experience with machine learning for time-series or spatial data, specifically regarding on-device model optimization and quantization.
• Background in signal processing, Kalman filtering, particle filters, or other probabilistic state estimation techniques.
• Experience with clustering algorithms and large-scale data analysis for algorithm development and performance evaluation.