Machine Learning PhD Intern

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. Since then, we've bootstrapped to a live product, secured a competitive SBIR grant from the U.S. National Science Foundation, deployed in multiple countries, and begun generating customer revenue.

About the Role

We're hiring a PhD intern to join the core R&D team at a pivotal moment. This internship is a chance to contribute to core algorithms, dig deep into a deployed product, and ship changes that reach enterprise customers, while also driving new research directions in spatial AI. You'll gain exposure to the full journey of research-to-production, working in a fast-paced, hands-on environment where your work makes a tangible impact.

You'll be joining us full-time, in-person internship based in Kendall Square, Cambridge, next to MIT and the Charles River. We expect the initial duration of the internship to be six months, but we will be open to extending that.

Responsibilities

Contribute to machine learning and signal processing algorithms for indoor positioning and perception.

Evaluate and improve models in production.

Run experiments on real-world customer data, analyze performance, and iterate to improve reliability and efficiency.

Collaborate with engineering and product to ship features to enterprise customers.

Qualifications

Currently enrolled in a PhD program (or recently graduated) in Computer Science, Electrical Engineering, Robotics, or a related field.

Strong foundations in at least one between machine learning, perception, sensor fusion, and / or signal processing. Experience or strong interest in spatial AI (3D vision, SLAM, mapping, sensor fusion, geometric deep learning, â?¦) is highly desirable.

Research track record of published work in top-tier CS / ML, vision, robotics, or related venues.

Excellent communication skills and ability to work in a small, fast-moving team.

Experience with Python.

Nice to have

Past startup experience

Ability to write high-quality, maintainable code.

Background in wireless localization, radar signal processing, or computer vision.

Experience developing and debugging models in real or simulated production environments.

Prior experience with deep learning applied to time-series data and / or transformer architectures.