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# Production Systems Engineer, AI Network

- **Company:** The Meta Game, Inc.
- **Location:** Menlo Park, CA, United States
- **Experience:** Expert
- **Salary:** $144,000.0 - $204,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computing Platforms, Systems Engineering, Computer Engineering, Data Centers, Data Visualization, Software Debugging, Linux, Network Interface Controllers, Firmware, Monitoring of Systems, Network Interface, Operational Databases, Rapid Prototyping Process, Remote Direct Memory Access, System Testing, Systems Integration, TCP/IP, Network Switches, Digital Access Carrier System, Computer Network Technologies, Application Specific Integrated Circuits, Break Fix, AI Platforms, Information Technology, Hardware Debugging
- **Published:** October 11, 2026
- **Apply:** https://www.juju.com/job/1_facebook2-1057437797094335

## About the Role

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 9.
6+ years of work experience in one or more domains such as: 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) 10.
Knowledge of server architecture and components 11.
Experience working with Linux 12.
Knowledge of TCP/IP and experience using iperf 13.
Hands-on troubleshooting and debug experience **Preferred Qualifications:** Preferred Qualifications: 14.
Experience working with large-scale deployments 15.
Experience working with Network Interface Cards (NICs) 16.
Experience working with RDMA/ RoCE 17.

## Description

**Summary:** 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 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.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 candidate should be 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. **Required Skills:** Production Systems Engineer, AI Network Responsibilities: 1.
Support the new AI platform introduction into Meta's fleet by driving scale up (e.g.
NVLink, XGMI) and scale out (e.g.
NICs) interface integration 2.
Develop an understanding of collective communication patterns and AI workloads to incorporate this as part of NPI 3.
Proactively create experiments and tooling to detect, reproduce, and diagnose hardware/firmware/software health issues 4.
Contribute to rapid prototyping and proof-of-concept efforts for future AI technology explorations 5.
Troubleshoot, diagnose, and root cause of system failures and isolate the components/failure scenarios while working with internal and external partners 6.
Develop visibility through data visualization and implement systemic solutions to hardware health issues 7.
Leverage production experience to drive both external and internal teams to continuously improve product quality **Minimum Qualifications:** Minimum Qualifications: 8.