AI/HPC Network Performance Engineer

Meta; Austin (TX); On-site; USD 184,000 - 257,000; Full time

Job summary

Meta's AI Training and Inference Infrastructure team in Austin is expanding its network fabric to connect thousands of GPUs with a lossless RDMA fabric.

You will design, deploy, and operate scalable networking systems to support massive AI training workloads, ensuring low latency, high throughput, and reliability across the data center.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related field.
• 8+ years of experience in system performance engineering or large-scale HPC/networking environments.
• Experience coding in Python, C++, Go.
• Experience deploying datacenter networks at scale.
• Experience with network automation software leveraging SDN principles.

Responsibilities

• Design, develop, test and operate networking systems to support large scale AI training jobs.
• Research, develop and deploy technologies and network topologies to evolve and scale AI networks.
• Work closely with hardware, software and sourcing teams to develop new networking solutions and influence the future of networking and its infrastructure.
• Define and develop optimized network automation tools and systems, including provisioning, monitoring, alarming, auto-remediation and more.
• Be oncall to learn from real world production challenges and take lessons to improve products.
• Provide guidance on network architecture including scale-up and scale-out topologies, transport protocols, and performance optimization techniques.

Skills

Python

C++

Go

Networking at scale

Network automation

On-call support

Education

Bachelor's degree in Computer Science or Computer Engineering

Tools

IB/RDMA/RoCE

Job description

Summary:

Meta's AI Training and Inference Infrastructure is growing exponentially to support ever increasing use cases of AI. This results in a dramatic scaling challenge that our engineers have to deal with on a daily basis. We need to build and evolve our network infrastructure that connects myriads of GPUs together. In addition, we need to ensure that the network is running smoothly and meets stringent performance and availability requirements of RDMA workloads that expects a lossless fabric interconnect. To improve performance of these systems we constantly look for opportunities across our infrastructure stack: network fabric and host networking, comms lib and scheduling infrastructure.

Required Skills:

AI/HPC Network Performance Engineer Responsibilities:

1. Design, develop, test and operate networking systems to support large scale AI training jobs




2. Research, develop and deploy numerous technologies and network topologies in order to evolve and scale our AI networks




3. Work closely with our hardware, software and sourcing teams to develop new networking solutions and influence the future of networking and its associated infrastructure




4. Define and develop optimized network automation tools and systems, including configuration, provisioning, monitoring, alarming, auto-remediation and more




5. Be oncall to learn from real world production challenges and take the lessons to improve current and future generation products




6. Provide guidance on network architecture including scale-up and scale-out topologies, transport protocols, and performance optimization techniques

Minimum Qualifications:

Minimum Qualifications:

1. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience




2. 8+ years of experience in system performance engineering, network infrastructure engineering, or a related field within large-scale distributed computing or HPC environments




3. Experience coding in languages like Python, C++, Go




4. Experience in designing, deploying and operating datacenter networks at scale




5. Experience in network automation software leveraging software defined networking principles

Preferred Qualifications:

Preferred Qualifications:

1. Understanding of AI training workloads and demands they exert on networks




2. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)




3. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)




4. 4+ years of experience working on networks supporting large scale training workloads




5. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies




6. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies




7. Experience working with IB/RDMA/RoCE Networks




8. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)




9. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)




10. Understanding of RDMA congestion control mechanisms on IB and RoCE Networks




11. Experience with scale-up and scale-out network fabric architectures

Public Compensation:

$184,000/year to $257,000/year + bonus + equity + benefits

Industry:

Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and
We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, or condition as an individual with a disability. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [e-mail].