Applied Scientist

Applied Scientist

Cartesian is building wireless foundation models to map the indoor world at scale.

We are tackling one of the biggest unsolved problems in the $35-trillion global retail industry: inventory visibility within stores. Our first-of-its-kind inventory intelligence product is enabling unprecedented indoor positioning and insights to solve this problem for retailers, starting with international fashion brands.

Our founders are an MIT engineering professor and alum who invented the award-winning patented technologies underlying Cartesian. Since spinning out in 2023, we’ve bootstrapped to a deployed product, secured the highly selective SBIR grant from the U.S. National Science Foundation, and are generating revenue from paying customers.

We’re now looking for a highly motivated, product-oriented Scientist to join our core R&D team at a pivotal moment in our growth. You'll have a direct impact on core algorithms, take ownership of new features, and shape the technical roadmap of a category-defining product. We move fast, care deeply about quality, and value people who take initiative and crave real-world impact. 

You’ll be joining us in-person in the heart of Kendall Square, Cambridge, next to MIT and the Charles River.

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

Qualifications

• PhD in computer science or related field.
• 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…. 
• Publications in top-tier ML, vision, or systems venues (e.g., ACL, NeurIPS, CVPR, ECCV, ICCV, MobiCom, MobiSys, MLSys, ICASSP).
• 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. 

Nice to have

• Past startup experience
• 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.