Applied ML/CS PhD Internship (6+ months)

About the Role

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

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

• 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 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.

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