Machine Learning Engineer 

About the Company

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. By fusing wireless signals and mobile computer vision, we provide a uniquely scalable and 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’re looking for a highly motivated, product-oriented Machine Learning Engineer 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

• BS/MS in computer science, electrical engineering, or related technical field.

• 3+ years of practical industry experience building end-to-end deep learning systems, from model design to dataset creation and experimentation with new ideas

• Proficiency in writing high-quality, maintainable production code, with strong software engineering fundamentals) testing, version control, CI/CD, performance optimization). 

• Strong communication skills and proven ability to collaborate effectively with cross-functional teams including backend, infrastructure, product and research. 

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

Nice to have

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

• Startup experience, especially in environments requiring rapid iteration, ownership, and end-to-end execution

• 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 or edge devices.

• 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).

Why Now

We’re a fast-moving MIT startup at an important inflection point for our product growth and direction. We are building a talent-dense team of engineers and applied researchers to solve hard, high-impact problems in retail operations.

You will have outsized ownership and autonomy. You will grow extremely quickly and make important contributions to our product, engineering culture, and company direction. We will push you to become a better engineer, and we will expect the same from you. 

Technology

• Backend: FastAPI, Python

• Data: Postgres, Blob Storage, Parquet

• Machine Learning: PyTorch, Ray

• Infrastructure: Azure, Kubernetes, Helm

• Frontend: Next.js, Typescript, Tailwind

• Mobile: Android, Kotlin