Fleet Operations Engineer
Join Ornn as a Fleet Operations Engineer to build and secure systems for GPU production in a fast-paced startup environment.
Posted by employer 2 weeks ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
What you'll build
- Build and operate low-level systems infrastructure
- Provision and manage virtualized GPU compute
- Write production-grade Python
- Secure the node fleet
- Own problems end to end
Must have
- Strong low-level systems fundamentals
- Excellent in Python
- Deep familiarity with Linux environments
- Effective communicator
- Genuine interest in AI hardware
Nice to have
- Virtualization experience
- Network security experience
Not disclosed in this posting: compensation, years of experience, visa sponsorship.
Benefits
Joblaze summary
The Fleet Operations Engineer at Ornn is responsible for establishing, debugging, and securing systems that facilitate GPU production. This role requires strong expertise in low-level systems, particularly within Linux environments, and proficiency in Python, with additional skills in virtualization and network security being advantageous. Ideal candidates are independent problem solvers with a solid understanding of AI hardware and a background in systems engineering. Ornn's lean team structure emphasizes the importance of technical quality in shaping user experience and operational efficiency.
Joblaze insights
Quick facts
- Is the Fleet Operations Engineer role remote?
- No — this is an on-site role in New York, United States.
- Where is the role based?
- Ornn is hiring for this position in New York, United States.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: KVM, Kubernetes, Linux, Python, QEMU, Rust.
- What seniority level is this role?
- Ornn targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Fleet Operations Engineer role at Ornn.
From the original posting
About the Role
We're hiring a Fleet Operations Engineer to stand up, debug, and secure the systems that get GPUs into production.
What You'll Do
Build and operate low-level systems infrastructure across Linux environments, from bare metal to VMs to orchestration.
Provision and manage virtualized GPU compute (KVM/QEMU, GPU passthrough) alongside Kubernetes and Slurm workloads.
Write production-grade Python daily and contribute to Rust services.
Secure the node fleet with network segmentation, firewalls, access control, and secure-by-default configuration.
Own problems end to end in a fast-paced environment with minimal hand-holding.
What We're Looking For
Requirements
Strong low-level systems fundamentals, including OS internals, performance, and debugging.
Excellent in Python.
Deep familiarity with Linux environments.
Effective communicator and independent problem solver. You will interface with customers, operators, and internal teams.
A genuine interest in AI hardware: GPUs, accelerators, and the systems that feed them.
Nice-to-Haves
Virtualization experience: KVM/QEMU, hypervisors, VM lifecycle management.
Network security experience: hardening exposed nodes, VPNs and zero-trust access, firewalls, locking down cluster access.
Why This Role Matters
At this stage, technical product quality and company credibility are tightly linked. The systems you build will shape how users experience the company and how fast the organization can operate.
Compensation and Benefits
Benefits include competitive salary, meaningful equity, health coverage, free meals, and additional benefits. This is a leadership role with significant strategic impact and equity upside.
Standard company text repeated across Ornn's postings is omitted here.
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