Jobs 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.

Conduct research and develop production algorithms for indoor positioning, spatial perception, sensor fusion, and spatial AI. The intern will run experiments on real-world customer deployments, analyze failures, improve ML and signal-processing pipelines, and collaborate with engineering and product teams to ship features to enterprise customers.

Own machine learning problems end to end, including data preparation, deep learning and model development, evaluation, deployment, monitoring, and production optimization. Build training, inference, and benchmarking pipelines for indoor positioning and item localization. Partner with applied scientists, engineering, and product teams to ship enterprise features, optimize accuracy, latency, coverage, and cost, and improve reusable ML infrastructure and architecture.

Supports business strategy and company operations through market research, customer and competitor analysis, financial modeling, reporting, process improvement, customer success, partner relations, product demos, onboarding, and fundraising activities. Works closely with the head of operations and founders to synthesize insights, inform strategic decisions, improve product-market fit, and support growth initiatives.