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Cartesian Systems

Indoor positioning AI for retail operations

Postdoctoral Associate

Computer VisionConfirmed live in the last 24 hours
Full-timeCambridge, MA, USANo salary listed

About the Job

Requirements

  • About to complete or recently completed a PhD program in Computer Science, Electrical Engineering, Robotics, or a related field.
  • Have a research track record of published work in top-tier computer science, machine learning, vision, robotics, or related venues.
  • Have strong foundations in at least one of machine learning, perception, sensor fusion, or signal processing.
  • Demonstrate research output, such as strong publications, open-source projects, or impactful applied work.
  • Be able to work in a small, fast-moving team.

Responsibilities

  • Explore new research directions in sensor fusion and spatial AI aligned with product needs.
  • Develop and improve algorithms for indoor positioning and spatial perception.
  • Run experiments on real-world customer deployments by collecting data, analyzing failures, proposing fixes, and validating improvements.
  • Contribute to production machine learning and signal processing pipelines, including modeling, evaluation, and deployment.
  • Collaborate with engineering and product teams to ship features to enterprise customers.

Desired Qualifications

  • Startup or early-stage company experience.
  • Experience shipping products, such as as part of internships.
  • Experience or strong interest in spatial AI, including 3D vision, simultaneous localization and mapping, mapping, sensor fusion, or geometric deep learning.

About the Company

Cartesian Systems

Indoor positioning AI for retail operations

Cartesian Systems builds an indoor spatial AI platform that gives retailers real-time visibility of in-store inventory. It fuses wireless signals with mobile computer vision to deliver accurate indoor positioning and actionable product location insights, enabling store staff to streamline operations without requiring extra infrastructure. Unlike many competitors, it uses an infrastructure-free approach that scales across stores and is already deployed by international fashion brands in multiple countries. Its goal is to improve in-store inventory visibility, reduce waste, and optimize retail operations at scale.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Cambridge, MA
Founded
2022

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