Staff Software Engineer (Infrastructure, Marimo)
CoreWeave
full-remoteleadpermanentbackenddevops Full remote 3 days ago via WTTJ
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PythonKubernetesDistributed SystemsConcurrencyFault ToleranceHigh AvailabilityGPU Resource AllocationNetworkingCloud InfrastructureFraud Prevention
About the role
Role Overview
Join Marimo as a Staff Software Engineer (Infrastructure) on the molab team. You will co-design and implement the backend architecture of molab, a cloud-hosted marimo notebook service, tackling greenfield problems around reliability and abuse prevention.
Key Responsibilities
- Co-design and implement molab’s backend architecture, with focus on:
- High availability
- Low latency
- Stability
- Fraud and abuse prevention
- Design molab to run on CoreWeave’s specialized Kubernetes-based clusters and integrate with CoreWeave object storage.
- Ensure efficient GPU utilization.
- Collaborate with the molab team to solve challenging greenfield problems and support rapid product growth.
Requirements
- 8+ years of software engineering experience.
- Experience building highly available, fault-tolerant systems.
- Strong computer systems expertise including:
- Concurrency (asynchronous programming)
- Parallel computing (threading, multiprocessing)
- Networking / IPC
- Experience with containerization and Kubernetes, including:
- scheduling
- distributed systems
- networked filesystems
- resource allocation
- cloud infrastructure
- Strong fundamentals that are language agnostic.
- Ability to communicate clearly (written and verbal).
Nice-to-haves
- Expertise in highly scalable cloud infrastructure.
- Empathy for AI/ML/data engineering researchers and practitioners.
- Experience with GPU resource allocation and sharing.
- Awareness of the Python AI/ML stack.
- Curiosity about how developers in AI/ML/data experiment with models and code.
- Strong interest in building performant, scalable tools for developers.
- Proficiency with Python and Python packaging.
About CoreWeave
CoreWeave builds cloud infrastructure focused on GPU-accelerated computing. It operates specialized Kubernetes-based clusters and related storage services to support high-performance workloads in data science and AI.
Scraped 6/11/2026