Fleet Operations Engineer
Ornn is building the financial infrastructure for the compute economy, providing reference pricing, market intelligence, capacity finance, and compute access for GPU compute. It serves buyers, sellers, and capital providers in the AI compute market, including institutions seeking to price, finance, and hedge compute the way commodities like oil are traded.
Maintainer signals as of 8/14/2026
Funding history
Projects
About Ornn
Ornn describes itself as 'The Foundation of the Compute Market,' building financial infrastructure to make GPU compute something that can be priced, financed, and hedged with confidence. Its flagship product is the OCPI (Ornn Compute Price Index), a reference price built on transaction-based data tracking live traded spot prices for GPU compute across hardware types such as H100, H200, B200, and B300, listed on Bloomberg. Ornn's product suite includes Ornn Compute Access (capacity for training, inference, and infrastructure-scale workloads) and Ornn Data (market measurement and intelligence covering pricing, volatility, supply, and demand). The company operates with a compliant architecture including complete KYC/AML protocols, combining physical and financial infrastructure into one compute platform. Ornn recently raised $33M led by A16Z and has been covered by The Economist, The Wall Street Journal, and Bloomberg. Its clients include buyers, sellers, and capital providers across the compute economy.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You stand up, debug, and secure the systems that get GPUs into production. You build and operate low-level infrastructure across Linux environments, provision virtualized GPU compute alongside Kubernetes and Slurm workloads, write production-grade Python, contribute to Rust services, secure the node fleet, and own operational problems end to end.
Requirements
- Strong low-level systems fundamentals, including operating system internals, performance, and debugging
- Excellent Python skills
- Deep familiarity with Linux environments
- Effective communication and independent problem-solving ability
- Genuine interest in AI hardware, GPUs, accelerators, and the systems that feed them
- Virtualization experience with KVM/QEMU, hypervisors, or VM lifecycle management is a plus
- Network security experience with exposed-node hardening, VPNs, zero-trust access, firewalls, and cluster access control is a plus
Responsibilities
- Build and operate low-level systems infrastructure across Linux environments
- Provision and manage virtualized GPU compute using KVM/QEMU and GPU passthrough
- Manage Kubernetes and Slurm workloads
- Write production-grade Python
- Contribute to Rust services
- Secure the node fleet with network segmentation, firewalls, and access control
- Apply secure-by-default configuration
- Own operational problems end to end
Benefits
- Meaningful equity
- Health coverage
- Free meals