NICs) interfaces for AI platforms Develop an understanding of collective communication patterns and AI workloads to incorporate this as part of NPI Proactively create experiments and tooling to detect, reproduce, and diagnose hardware/firmware/software issues Contribute to prototyping and proof-of-concept efforts for future technology explorations in the AI space Troubleshoot, diagnose, and root-cause system failures and isolate the components/failure scenarios while working with internal and external partners Develop visibility through data visualization and implement systemic solutions to hardware health issues Leverage production experience to drive external and internal teams to continuously improve product qualityBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of work experience in one or more domains such as: AI/ML/HPC network evaluation and tuning, Network ASIC/Platform development (silicon/switch platform design or bring-up or characterization), Network product deployment and customer support (switches, NICs), Interconnect technologies (e.g., optics, DAC) Knowledge of TCP/IP and experience in using tools like iperf Knowledge of server architecture and components Experience working with Linux Hands-on troubleshooting and debugging experience Experience leading projects with large teams Understanding of AI training process and various scale-out topologies Experience working with RDMA/RoCE, including scale-out networks Experience working with AI server systems Experience working with large-scale deployments Experience working with Network Interface Cards (NICs)Meta builds technologies that help people connect, find communities, and grow businesses. RTP Engineers have a large swath of cross-functional partners they work closely with, e.g., HW/SW co-design teams, hardware designers, networking teams, system manufacturers, component vendors, capacity engineering, production engineering, production services, and data center operations teams to enable new systems that will be deployed in our production data centers.