Cartesian is looking to solve the problem of in-store inventory visibility in the $35T global retail industry by building spatial intelligence for indoor environments to drive operational efficiency.
Requirements
- 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
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.
Other
- High Ownership, Relentless Problem Solver: You are a generalist who can tackle unfamiliar problems across our stack (infra, data, ML, APIs).
- Good Taste: You default to simple, maintainable solutions.
- Team Player and Low Ego: Your decision-making centers around team success rather than being “right”.
- Growth Oriented: You have a track record of picking up new skills and growing quickly.
- Work in-person 5 days a week in Kendall Square, right next to MIT and the Charles River.
