Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Go @ 3
Linux @ 3
Python @ 3
Distributed Systems @ 3
Networking @ 3
Debugging @ 3
GPU @ 3
Observability @ 3
AI @ 3
InfiniBand @ 3
Performance Analysis @ 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
The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI's compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads.
This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure.
About the Role
We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations.
You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale.
Responsibilities
- Design, build, and operate networking systems that support large-scale AI training and inference infrastructure.
- Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems.
- Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure.
- Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation.
- Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-performance GPU interconnects.
- Define and operationalize networking protocols, readiness criteria, and continuous validation systems.
- Partner closely with compute, storage, hardware, and infrastructure teams to ensure networking scales predictably with fleet growth.
- Contribute to architecture decisions around topology design, capacity planning, failure domains, and network reliability.
- Diagnose complex distributed systems and networking issues across large heterogeneous compute environments.
Requirements
- Experience building or operating large-scale networking or distributed systems infrastructure.
- Comfortable working close to the hardware/software boundary.
- Experience with Linux networking, kernel systems, NICs, RDMA, or performance-sensitive infrastructure software.
- Experience with high-performance networking technologies such as InfiniBand, RoCE, DPDK, or large-scale Ethernet fabrics.
- Experience with datacenter networking, WAN systems, or host networking stacks.
- Strong ability to debug complex systems and performance bottlenecks across multiple layers of the stack.
- Comfortable writing production software in languages such as C++, Python, or Go.
- Strong systems fundamentals across networking, operating systems, distributed systems, or infrastructure engineering.
- Motivation to build infrastructure that directly accelerates frontier AI research and deployment.
Benefits
- Base pay range listed: $230K – $342K; offers equity and additional compensation components.
- Medical, dental, and vision insurance with employer contributions to Health Savings Accounts.
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses.
- 401(k) retirement plan with employer match.
- Paid parental, medical, and caregiver leave (details in posting).
- Flexible PTO for exempt employees and paid time off for non-exempt employees.
- 13+ paid company holidays and additional office closures.
- Mental health and wellness support; employer-paid basic life and disability coverage.
- Annual learning and development stipend; daily office meals and meal delivery credits as eligible.
- Relocation support for eligible employees.
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 AI capabilities and seek to safely deploy them to the world through our products. OpenAI is an equal opportunity employer and provides reasonable accommodations to applicants with disabilities.