Meta is seeking a Systems Engineer to join our Release to Production New Product Introduction (RTP-NPI) team working on AI/ML initiatives supporting large-scale AI training and inference. Our servers and data centers are the foundation upon which our rapidly scaling infrastructure operates efficiently to deliver our innovative services. The RTP team is responsible for the end-to-end hardware lifecycle of all Meta servers, including prototyping of experimental HW, pre-production hands-on system and hardware debugging and stress testing, enabling production-ready system monitoring, automated provisioning and automated remediation of issues, ultimately certifying new platforms for mass production for AI at datacenter scale. RTP Engineers have a large swath of XFN 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. We are looking for a candidate who can support scale up and scale out network technologies for Meta AI systems that are powering Meta’s tremendous leaps in the AI space. The ideal candidate is knowledgeable about network technologies (NICs, Switches, Optics, DACs, Protocols-TCP/IP, RDMA) and has hands-on experience supporting them through at least a couple of hardware/software (firmware, driver) lifecycle phases: design and bring-up, server integration, system validation, supporting customer deployment, production issue triage, rolling out new features in FW/Driver.

Responsibilities

Lead integration of scale up (e.g. NVLink, XGMI, RoCE) and scale out (e.g. NICs) interfaces for AI platforms
Develop an understanding of collective communication patterns and AI workloads, and incorporate this as part of NPI
Proactively create experiments and tooling to detect, reproduce, and diagnose hardware/firmware/software issues
Contribute to enabling hacks for future technology explorations in 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 quality

Minimum Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Bachelor’s degree in Engineering or Computer Science
6+ years of work experience in one or more domains such as: AI/ML/HPC network evaluation/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

Preferred Qualifications

Experience with Python scripting
Experience working with large-scale deployments
Experience working with RDMA/RoCE, including scale-out networks
Experience working with AI server systems
Experience working with Network Interface Cards (NICs)

$173,000/year to $245,000/year + bonus + equity + benefits

Production Systems Engineer, Fleet AI Systems

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