Ai Engineer • Mid-Level

Who you are

You have a strong background in high-performance computing and networking, with experience in building and optimizing systems that support AI workloads. Your expertise in Linux and Python allows you to troubleshoot and enhance system performance effectively. You understand the intricacies of RDMA workloads and are familiar with loss-less fabric interconnects, ensuring that network infrastructure meets stringent performance and availability requirements.

You are skilled in using TensorFlow and Kubernetes, which enables you to manage and deploy AI models efficiently. Your experience with Docker helps you create and manage containerized applications, ensuring smooth integration and deployment across various environments. You thrive in collaborative settings, working closely with cross-functional teams to address scaling challenges and improve system performance.

What you'll do

In this role, you will be responsible for building and evolving Meta's network infrastructure that connects various training accelerators like GPUs. You will ensure that the network operates smoothly and meets the performance requirements for AI workloads. Your daily tasks will involve identifying opportunities for performance improvements across the stack, including network fabric, host networking, and scheduling infrastructure.

You will collaborate with engineers to tackle scaling challenges and implement solutions that enhance the overall efficiency of the AI Training and Inference Infrastructure. Your role will also involve monitoring system performance and availability, troubleshooting issues, and optimizing configurations to meet the demands of rapidly growing AI use cases.

What we offer

Meta provides a dynamic work environment where innovation is encouraged. You will have the opportunity to work on cutting-edge technologies and contribute to projects that have a significant impact on the future of AI. The company offers competitive compensation and benefits, fostering a culture of collaboration and continuous learning. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.