Cartesian is tackling one of the biggest unsolved problems in the $35-trillion global retail industry: inventory visibility within stores
Requirements
- Deep understanding and practical experience in at least one of the following areas: machine learning, signal processing, transformers, probabilistic models (e.g., state estimation, EKF, …), SLAM, mapping, localization, MDP, GNNs, 3D reconstruction, sensor-fusion, dead reckoning….
- Ability to write high-quality, maintainable code
- Publications in top-tier ML, vision, or systems venues (e.g., ACL, NeurIPS, CVPR, ECCV, ICCV, MobiCom, MobiSys, MLSys, ICASSP)
- Familiarity with cloud-based model training and inference
- Background in wireless localization, radar signal processing, or computer vision
- PhD in computer science or related field
- Past startup experience
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
Other
- PhD in computer science or related field
- Excellent communication skills and ability to collaborate across disciplines
- Thrive in fast-paced, dynamic environments and take pride in producing high-quality work
- Industry experience in applied software or ML engineering
- Ability to work in-person in the heart of Kendall Square, Cambridge, next to MIT and the Charles River
