Machine Learning Scientist
Cartesiansystems · Cambridge, MA
About this role
**Machine Learning Scientist** **About the Company** Cartesian is building spatial intelligence for indoor environments to drive operational efficiency. They’re tackling in-store inventory visibility by delivering accurate indoor positioning and actionable product location insights—helping retailers streamline operations, optimize workflows, and reduce inefficiencies. Their platform fuses wireless signals and mobile computer vision and is infrastructure-free, already deployed by international fashion brands. Founded in 2023, Cartesian is scaling a live product deployed in over a dozen countries. **About the Role** Cartesian is seeking a product-oriented Machine Learning Scientist to join their core R&D team. You’ll directly impact key positioning algorithms and models, take ownership of new features, and help shape the technical roadmap for a category-defining product. The team moves fast, prioritizes quality, and values initiative and real-world impact. This role is **in-person** in **Kendall Square, Cambridge** (next to MIT and the Charles River). **Responsibilities** - Design, develop, and deploy ML models for indoor positioning and perception - Optimize model architectures for performance and efficiency - Develop tools and datasets to benchmark performance in real-world and at scale settings - Translate research into production pipelines - Collaborate with engineering and product to ship features to enterprise customers **Qualifications** - PhD in computer science, electrical engineering, or a related field - Deep understanding and hands-on experience with ML models for time-series data, including transformer-based architectures and probabilistic models (e.g., state estimation) - Publications in top-tier ML, vision, or systems venues (e.g., ACL, NeurIPS, CVPR, ECCV, ICCV, MobiCom, MobiSys, MLSys, ICASSP, ICML, ICRL, ICRA, IROS) - Ability to write high-quality production code - Excellent communication skills and ability to collaborate across disciplines - Thrives in fast-paced, dynamic environments and takes pride in high-quality work **Nice to have** - Past startup experience - Industry experience in applied software or ML engineering - Familiarity with cloud-based model training and inference - Experience optimizing and deploying ML models in mobile environments - Background in wireless localization or radar signal processing - Experience with computer vision or multi-sensor fusion (e.g., 2D/3D perception, pose estimation, tracking, SLAM)
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