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About Cartesian 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, infrastructure-free solution already deployed by international fashion brands.
Founded by an MIT engineering professor and alumni behind award-winning, patented core technologies, Cartesian spun out in 2023. Originally backed by a U.S. National Science Foundation SBIR Award, we’ve bootstrapped to a live product now deployed in multiple countries and are scaling aggressively.
About The Role
We’re a small, technical team and we’re always looking for exceptional people to join us. If you’re a strong engineer excited about the problems below, we want to hear from you. We’ll figure out the right fit together.
For summer/fall 2026, we’re in particular looking for motivated upper-level undergraduates or graduate students.
What We Work On
We’re Scaling a Platform That Processes Billions Of Wireless Signal Readings To Locate Products Inside Retail Stores Across Multiple Countries. Some Of The Problems Our Engineering Team Works On
- Product development: Shipping dashboards, APIs, and tools that help retail operations teams make better decisions every day
- Data infrastructure: Building efficient pipelines to ingest, process, and serve TB-scale datasets with tight latency and cost constraints
- ML in production: Training, deploying, and monitoring ML models that run on mobile devices and cloud infrastructure
- Mobile and edge: Design mobile (Android) SDKs that integrate with enterprise PDAs and wireless scanners.
- Platform reliability: Scaling Kubernetes-based infrastructure on Azure to support rapid international deployment
- Indoor positioning at scale: Fusing noisy RFID and computer vision data into accurate, real-time product locations across hundreds of stores
About You
- Exceptional engineer: You write clean, effective code and default to simple, maintainable solutions. You have good instincts for when complexity is worth it and can articulate why.
- High ownership: You take problems end-to-end, and make sure they get done. You pragmatically fix issues when you find them, rather than waiting for someone else to do so. You feel responsible for the broader system, not just wants written on your ticket.
- Fast learner: You are a generalist who can tackle unfamiliar problems across our stack (infra, data, ML, APIs). You pick up new tools, domains, and skills quickly. You actively seek feedback, and take initiative to expand your impact.
- Team-first: Your decisions center around team success and working towards the best ideas. You’re a good listener, collaborator, and communicator. Low ego, high standards.
Technology
Backend: FastAPI, Python
- Data: Postgres, Blob Storage, Parquet
- ML: PyTorch, Ray
- Infrastructure: Azure, Kubernetes, Helm
- Frontend: Next.js, TypeScript, Tailwind
- Mobile: Android, Kotlin
Why Cartesian
- Work on hard, real-world problems with immediate and visible impact
- Join a small, highly technical team with significant ownership and autonomy
- Build systems that are deployed and used globally
- Collaborative, thoughtful, low-ego culture focused on learning and execution
- In-person team culture in the heart of Kendall Square, Cambridge
If You’re Not Sure You’re a Perfect Fit
We know that no one checks every box—and we don’t expect you to. If this role sounds exciting to you, and you think you could contribute to Cartesian’s mission, we encourage you to apply even if your experience doesn’t perfectly match the description. We care deeply about people who are curious, thoughtful, and motivated to learn, and we believe strong teams are built from a diversity of backgrounds, experiences, and perspectives.
Interview Process
- Screen (15–20 min): Sync on the role and your interests.
- Technical interviews (2 rounds): Project deep-dive, coding (not leetcode).
- Behavioral Interview
- References
- Offer
Salary Range
$50,000 – $77,000 USD
