Postdoctoral Associate
Cartesian Systems · Cambridge
About Cartesian
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.
About the Role
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
What You’ll Do
- 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: collect data, analyze failures, propose fixes, and validate improvements
- Contribute to production ML and signal processing pipelines (modeling, evaluation, deployment)
- Collaborate with engineering and product to ship features to enterprise customers
Qualifications
- About to complete or recently completed a PhD program in Computer Science, Electrical Engineering, Robotics, or a related field.
- Research track record of published work in top-tier CS/ML, vision, robotics, or related venues.
- Strong foundations in at least one of: machine learning, perception, sensor fusion, and/or signal processing.
- Demonstrated research output (e.g., strong publications, open-source projects, or impactful applied work)
- Excellent communication skills and ability to work in a small, fast-moving team.
- Curiosity, ownership, and a bias toward action and real-world impact
Nice to Have
- Startup or early-stage company experience
- Experience shipping products (e.g., part of internships)
- Experience or strong interest in spatial AI (3D vision, SLAM, mapping, sensor fusion, geometric deep learning, …) is highly desirable.
Why Cartesian
- Work on hard, real-world problems with immediate and visible impact
- Join a small, highly technical team with significant ownership and autonomy
- Build systems that are deployed and used globally
- Collaborative, thoughtful, low-ego culture focused on learning and execution
- In-person team culture in the heart of Kendall Square, Cambridge
Interview Process
- Introductory call to assess motivation and overall fit (20m)
- Technical interview focused on past projects (60m)
- Technical design interview (45m)
- Coding interview (45m)
- Meet Prof. Fadel Adib (20m)
- Meet the team and references
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