Associate Research Scientist at Cartesian in Cambridge, MA

Summary: Cartesian is building spatial intelligence for indoor environments to drive operational efficiency. They are seeking a highly motivated, product-oriented Associate Research Scientist to join their core R&D team and work on core algorithmic problems, translating research prototypes into robust production pipelines. Responsibilities: - Work on core algorithmic problems that blend modeling, estimation, and perception - Build and run experiments and benchmarks on real data from live deployments - Translate research prototypes into robust production pipelines (mobile, edge, cloud) in collaboration with engineering - Work across engineering and product to define and deliver new features for enterprise customers - Monitor, analyze, and improve system performance in real world conditions and scale - Develop datasets, metrics, and tools that help us measure and improve performance - Help shape new product capabilities and directions as we expand - Own problems end to end from framing to deployment Required Qualifications: - BS/MS in computer science or related field - Deep understanding and practical experience in at least one of the following areas: machine learning, signal processing, transformer models, probabilistic models (e.g., state estimation), SLAM, MDP, GNNs, 3D reconstruction, sensor-fusion models, … - Ability to write high-quality, maintainable code - Excellent communication skills and ability to collaborate across disciplines - Thrive in fast-paced, dynamic environments and take pride in producing high-quality work Preferred Qualifications: - Past startup experience - Publications in top-tier ML, vision, or systems venues (e.g., ACL, NeurIPS, CVPR, ECCV, ICCV, MobiCom, MobiSys, MLSys, ICASSP) - Industry experience in applied software or ML engineering - Familiarity with cloud-based model training and inference - Background in wireless localization, radar signal processing, or computer vision Required Skills: Machine Learning, Signal Processing, Transformer Models, Probabilistic Models, State Estimation, Simultaneous Localization, Mapping (SLAM), Markov Decision Processes (MDP), Graph Neural Networks (GNNs), 3D Reconstruction, Sensor Fusion Models, High-Quality Code Writing