Applied ML & Spatial AI PhD Internship — Cambridge

Cartesian Systems; Cambridge (MA); On-site; USD 40,000 - 60,000; Full time

Benefits offered by this job

Collaborative, thoughtful culture

Significant ownership and autonomy

Work on real-world problems with immediate impact

Job summary

Cartesian Systems is offering an Applied ML/CS PhD Internship in Cambridge, MA, to contribute to core algorithms and impact enterprise customers. This full-time, in-person role at the Cartesian HQ includes exploring sensor fusion, developing algorithms, and running real-world experiments.

The ideal candidate is currently enrolled in a PhD program in Computer Science or related fields with a strong research background. Join our small, innovative team and make a tangible impact in the spatial AI domain.

Qualifications

• Research track record of published work in top-tier CS/ML, vision, robotics, or related venues.
• 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.

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, and propose fixes.

Skills

Machine learning

Perception

Sensor fusion

Signal processing

Education

Currently enrolled in a PhD program in Computer Science, Electrical Engineering, Robotics or a related field

Job description

Cartesian Systems is offering an Applied ML/CS PhD Internship in Cambridge, MA, to contribute to core algorithms and impact enterprise customers. This full-time, in-person role at the Cartesian HQ includes exploring sensor fusion, developing algorithms, and running real-world experiments.

The ideal candidate is currently enrolled in a PhD program in Computer Science or related fields with a strong research background. Join our small, innovative team and make a tangible impact in the spatial AI domain.