Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
Debugging @ 6
Distributed Systems @ 3
GPU @ 3
InfiniBand @ 3
Linux @ 3
Networking @ 3
Observability
Python @ 6
SQL @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
About the Team
The Hardware Health and Observability team owns the end-to-end health lifecycle of OpenAI’s global compute fleet.
Our mission is to maximize healthy, usable compute across accelerator vendors, generations, cloud providers, and regions through reliable health signals, automated remediation, and scalable operational tooling.
We build the systems that observe, detect, remediate, and verify hardware issues across GPUs, CPUs, networking, and platform infrastructure, enabling frontier model training and inference workloads to run reliably at hyperscale. We are the last line of defense for the success of OAI’s production and research workloads.
About the Role
On the Hardware Health and Observability team, you’ll build critical infrastructure that keeps OpenAI’s largest compute clusters healthy and operational at scale.
Even small numbers of unhealthy systems can impact large-scale training and inference workloads. This team focuses on minimizing downtime, improving fleet efficiency, and ensuring compute resources remain continuously available to researchers and product teams.
Engineers on this team own problems end-to-end, from defining health signals and debugging failures to building automated remediation systems that operate across millions of GPUs globally.
In this role, you will:
- Define and maintain health signals across GPUs, CPUs, networking, and platform infrastructure.
- Build and evolve health checks that detect, remediate, and verify failures at scale.
- Ensure critical health checks execute with minimal latency to maximize workload uptime.
- Investigate hardware failures and system-level issues across large-scale compute environments.
- Own node lifecycle workflows including drain, quarantine, repair, RMA, and return-to-service processes.
- Build automation and tooling that enables global cluster management with minimal manual intervention.
- Partner with workload, reliability, and provider teams to integrate health signals into training and inference systems.
Requirements
You might thrive in this role if you have:
- 7+ years of industry experience in software or infrastructure engineering.
- Strong proficiency with Python and shell scripting.
- Experience building large-scale distributed systems or infrastructure platforms.
- Comfort digging into noisy operational data using SQL, PromQL, or similar tooling.
- Experience building reproducible analyses and operational tooling.
- Strong systems debugging and operational instincts with an ownership mindset.
Bonus if you have
- Experience with low-level hardware systems and Linux tooling (e.g. PCIe, InfiniBand, RoCE, networking, power management, kernel performance tuning, FW/SW debugging).
- Experience operating or debugging large-scale GPU or accelerator clusters.
- Expertise in network operations, observability, or systems telemetry.
- Experience with automated remediation systems or fleet lifecycle management.
- Experience improving reliability, utilization, or workload uptime in distributed compute environments.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products.
We are an equal opportunity employer.
Background checks for applicants will be administered in accordance with applicable law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via the provided link.
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.