Demo

Software Engineer

cartesiansystems
Cambridge, MA Full Time
POSTED ON 9/1/2026
AVAILABLE BEFORE 11/1/2026

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 are seeking an exceptional engineer to help us 1000x our product scale. You’ll have full ownership over major features, wear a lot of hats, and work alongside a highly technical team of engineers and applied researchers.

We work in-person 5 days a week in Kendall Square, right next to MIT and the Charles River.

Responsibilities

  • Design and implement reliable, scalable, and cost-effective backend systems and new features across our API, data, ML, and DevOps platforms.

  • Be independent and own major features from ideation through deployment.

  • Contribute to engineering best practices, planning, roadmap, and culture.

Technical Qualifications

Our highest priority is finding exceptional individuals with a strong sense of simple, effective software design. However, the strongest candidates will have 3 years of demonstrated expertise in some of the following areas:

  • Building scalable web services and intuitive APIs with modern Python

  • Distributed systems for compute-heavy ML workloads

  • Data structures, database query optimization and efficient data pipelines for TB-scale datasets.

  • Developing dashboards for internal and external users

  • Managing cloud infrastructure using IaC tools (ideally on Azure), including Kubernetes, Helm, Terraform

  • Improving CI/CD pipelines to help us ship quickly and with high quality

About You

  • High Ownership, Relentless Problem Solver: You are a generalist who can tackle unfamiliar problems across our stack (infra, data, ML, APIs). You put in the hard work upfront and drive to deliver. You pragmatically fix issues when you find them, rather than waiting for someone else to do so.

  • Good Taste: You default to simple, maintainable solutions. You think carefully about how system design impacts customer experience, engineering velocity, and operational complexity. You have good instincts for when added complexity is actually worth it. Most importantly, you are able to articulate your reasoning to help the team make better decisions.

  • Team Player and Low Ego: Your decision-making centers around team success rather than being “right”. You give 100% and expect the same from others. You are a good leader, listener, mentor, and doer.

  • Growth Oriented: You have a track record of picking up new skills and growing quickly. You are a lifelong learner and actively seek critical feedback from others. You’re defined by where you’re going, not where you started.

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

Interview Timeline

Stage 1: Intro Screen with Co-Founder (30 minutes)

Stage 2: Technical Background (2 hours)

  1. Project Deep-Dive

  2. Coding Exercise (half offline, half live)

Stage 3: Design Behavioral (2.5 hours)

  1. System Design

  2. Meet CEO & Engineering Team

  3. References

Stage 4: Offer!

Salary : $35

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