Applied Research Scientist

About the Company

Cartesian is building spatial intelligence for indoor environments to drive operational efficiency.

We’re tackling one of the biggest challenges in the $35T global retail industry: in-store inventory visibility. Our platform delivers accurate indoor positioning and actionable product location insights, helping retailers streamline operations, optimize workflows, and reduce inefficiencies. By fusing wireless signals and mobile computer vision, we provide a uniquely scalable and infrastructure-free solution already deployed by international fashion brands.

Founded by an MIT engineering professor and alum behind the award-winning, patented core technologies, Cartesian spun out in 2023. Originally backed by the prestigious SBIR Award from the US National Science Foundation, we've bootstrapped to a live product that's now deployed in over a dozen countries and have been aggressively scaling in the market.

About the role

We are now looking for an Applied Research Scientist to join our core R&D team in a pivotal moment in our growth. We are not tied to a specific checklist of credentials; what matters is your ability to design and run experiments, learn quickly, and turn ideas into working systems. The role is hands-on and end-to-end: you might collect and curate data, prototype and productionize models, analyze results to drive algorithmic improvements, or collaborate closely with engineering and business teams to ship features that matter. You will help shape the technical direction of the product from day one. We move quickly, expect high-quality work, and value initiative and real impact.

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

You will…

• 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, engineering or related field, or MSc. and 3 years of applied experience, preferably in fast moving environments and strong teams
• Ability to understand complex systems, break down problems, and design clear experiments
• Deep understanding and practical experience inof at least one of the following areas: machine learning, and/or signal processing algorithms, transformer models , probabilistic models (e.g., state estimation), SLAM, MDP, GNNs, 3D reconstruction, sensor-fusion models, …. 
• 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. 
• Curiosity, initiative, and a desire to work on problems that do not have clean answers while still able to focus on real-world impact
• Thrive in fast-paced, dynamic environments and take pride in producing high-quality work.

Interview Process

1. Intro call to assess motivation and fit
2. Technical discussion about your past work focusing on real-world impact, decision process, tradeoffs
3. Applied coding session
4. Brainstorming session with the team
5. Meet the team, chat with a founder, and submit references