Meta is seeking an Engineer to join our Release to Production (RTP) team working on AI/ML initiatives. 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 pre-production hands-on system and hardware debugging and stress testing, enabling production-ready system monitoring, automated provisioning and automated remediation of issues. RTP team also helps in exploring, developing and productizing high-performance software and hardware technologies for AI at datacenter scale. RTP-NPI team in RTP work closely with 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 also work across service and hardware architectures for new AI systems, build prototypes to demonstrate the value, enable go/no-go decisions and optimize these systems in production.

Production Systems Engineering, RTP Responsibilities

• Interact with external vendors and internal hardware, mechanical, power, thermal, manufacturing and software engineers to understand system architecture to develop and execute the test suites for various architectures


• Working with end users and cross functional partners to execute full product life-cycles (prototyping, deployment and support)


• Proactively create experiments and tooling to detect and diagnose hardware/firmware/software health issues


• Troubleshoot, diagnose and root cause of system failures and isolate the components/failure scenarios while working with internal & external stakeholders


• Continuously improve cross functional collaboration with partnership teams to improve quality and efficiency for NPI

Minimum Qualifications

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


• Demonstrated experience in one or more domains such as ASIC development (Silicon design or bring up or characterization), compute (ARM, x86), AI-ML hardware/software (GPUs, TPUs)


• Knowledge of server architecture and components across Compute/AI systems


• Experience in strategic implementation and planning for risk and growth


• Developing and managing requirements, and making data-driven decisions

Preferred Qualifications

• 10+ years of experience with some of the following modules/domains: Servers, CPU, GPU, DRAM (DDR4/5 or HBM), PCIe, Network


• 5+ years of experience in hands-on SW/FW/HW areas to build systems/products for data-center environments, consumer devices/HW, or similar

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