Teams at Cartesian

Design, develop, and deploy machine learning models for indoor positioning and perception. Optimize model architectures, create real-world benchmarking tools and datasets, translate research into production pipelines, and collaborate with engineering and product teams to ship enterprise features. The role requires advanced expertise in time-series machine learning, transformer and probabilistic models, production coding, and research publication, with opportunities to apply computer vision, wireless localization, sensor fusion, and mobile ML deployment.

Design, develop, optimize, and deploy machine learning models for indoor positioning and perception. Build real-world benchmarking tools and datasets, translate research into production pipelines, and collaborate with engineering and product teams to deliver enterprise features. The role requires advanced expertise in time-series machine learning, transformer architectures, probabilistic models, and production software development, with opportunities to apply computer vision, wireless localization, radar processing, and sensor fusion.

Conduct research in sensor fusion and spatial AI, develop indoor positioning and spatial perception algorithms, run experiments on customer deployments, analyze failures, and improve production machine learning and signal processing pipelines. The role collaborates with engineering and product teams to ship enterprise features and requires a PhD in computer science, electrical engineering, robotics, or a related field.