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. Leveraging wireless signals, we provide a uniquely scalable, 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.
We are looking for a Postdoctoral Associate to join Cartesian at an exciting moment in our growth. This opportunity 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. This is a hands-on role at the intersection of machine learning, perception, estimation, and signal processing, with direct impact on a deployed enterprise product. You’ll gain exposure to the full journey of research in production, working in a fast-paced, hands-on environment where your work makes a tangible impact.
This role is product- and impact-driven. Due to the IP-sensitive nature of the core models and algorithms, this role is not expected to involve publications.
Location: In-person at the Cartesian HQ in Kendall Square, Cambridge.
Role type: Full-time, PhD postdoctoral position
Duration: Minimum 1 year
Job details are sourced from the employer's original posting.
Open job postingAbout the company
Cartesian Systems is a company focused on advanced robotics and AI, likely developing solutions in areas such as machine learning, perception, and sensor fusion. Their work appears to be at the cutting edge of computer science and engineering research.