Machine Learning Scientist - Cartesian (MIT Startup)

Qualifications

• PhD in computer science, electrical engineering, or related field
• Deep understanding and hands-on experience in machine learning models for time-series data, including both transformer-based architectures and probabilistic models (e.g., state estimation)
• Publications in top-tier ML, vision, or systems venues (e.g., ACL, NeurIPS, CVPR, ECCV, ICCV, MobiCom, MobiSys, MLSys, ICASSP, ICML, ICRL, ICRA, IROS)
• Ability to write high-quality production code
• Excellent communication skills and ability to collaborate across disciplines
• Thrive in fast-paced, dynamic environments and take pride in producing high-quality work
• Past startup experience
• Industry experience in applied software or ML engineering
• Familiarity with cloud-based model training and inference
• Experience in optimizing and deploying ML models in mobile environments
• Background in wireless localization or radar signal processing
• Experience with computer vision or multi-sensor fusion techniques (e.g., 2D/3D perception, pose estimation, tracking, SLAM)

Responsibilities

• You'll have a direct impact on key positioning algorithms & models, take ownership of new features, and help shape the technical roadmap of a category-defining product
• Design, develop, and deploy ML models for indoor positioning and perception
• Optimize model architectures for performance and efficiency
• Develop tools and datasets to benchmark performance in the real world and at scale
• Translate research into production pipelines
• Collaborate with engineering and product to ship features to enterprise customers

Full Description

Cartesian is building machine learning systems to map the indoor world at scale using wireless signals and mobile computer vision.

We are tackling one of the biggest unsolved problems in the $35-trillion global retail industry: inventory visibility within stores. Our first-of-its-kind inventory intelligence product is enabling unprecedented indoor positioning and insights to solve this problem for retailers, starting with international fashion brands.

Our founders are an MIT engineering professor and an alum who invented the award-winning patented technologies underlying Cartesian. Since spinning out in 2023, we’ve bootstrapped to a deployed product, secured the highly selective SBIR grant from the U.S. National Science Foundation, and are generating revenue from paying customers.

About the Role

We’re looking for a highly motivated, product-oriented Machine Learning Scientist to join our core R&D team at a pivotal moment in our growth. You'll have a direct impact on key positioning algorithms & models, take ownership of new features, and help shape the technical roadmap of a category-defining product. We move fast, care deeply about quality, and value people who take initiative and crave real-world impact.

You’ll be joining us in-person in the heart of Kendall Square, Cambridge, next to MIT and the Charles River.

Responsibilities

• Design, develop, and deploy ML models for indoor positioning and perception.

• Optimize model architectures for performance and efficiency.

• Develop tools and datasets to benchmark performance in the real world and at scale.

• Translate research into production pipelines.

• Collaborate with engineering and product to ship features to enterprise customers.

Qualifications

• PhD in computer science, electrical engineering, or related field.

• Deep understanding and hands-on experience in machine learning models for time-series data, including both transformer-based architectures and probabilistic models (e.g., state estimation).

• Publications in top-tier ML, vision, or systems venues (e.g., ACL, NeurIPS, CVPR, ECCV, ICCV, MobiCom, MobiSys, MLSys, ICASSP, ICML, ICRL, ICRA, IROS).

• Ability to write high-quality production code.

• Excellent communication skills and ability to collaborate across disciplines.

• Thrive in fast-paced, dynamic environments and take pride in producing high-quality work.

Nice to have

• Past startup experience

• Industry experience in applied software or ML engineering.

• Familiarity with cloud-based model training and inference.

• Experience in optimizing and deploying ML models in mobile environments.

• Background in wireless localization or radar signal processing

• Experience with computer vision or multi-sensor fusion techniques (e.g., 2D/3D perception, pose estimation, tracking, SLAM).