Applied ML/CS PhD Internship (6+ months)

Cartesian SystemsCambridge, MA
Onsite

About The Position

We are looking for an Applied ML/CS PhD intern to join Cartesian at an exciting moment in our growth. 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. 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 internship is product- and impact-driven. Due to the IP-sensitive nature of the core models and algorithms, the internship is not expected to involve publications. Location: In-person at the Cartesian HQ in Kendall Square, Cambridge. Internship type: Full-time, PhD internship. Duration and timing: 12–24 weeks, Summer 2026; flexible start dates.

Requirements

  • Currently enrolled in 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 Haves

  • 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.

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: 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

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What This Job Offers

Job Type

Full-time

Career Level

Intern

Education Level

Ph.D. or professional degree

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