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Salary
≈ $198k – $384k per year (Estimated)
Location
In office (Menlo Park)
Seniority
Staff · 8+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Oct 2, 2026. Meta scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Meta Platforms is an American technology company founded in 2004 as Facebook and renamed in 2021 to signal its investment in immersive computing. It operates the largest family of social and messaging applications in the world, comprising Facebook, Instagram, WhatsApp, Messenger and Threads, and earns almost all of its revenue from advertising sold against that audience. Headquartered in Menlo Park, California, the company also develops the open Llama language models and the Reality Labs division behind Quest headsets and Ray-Ban smart glasses.
Meta is seeking a Production Systems Engineer to join our Hardware Design and Release to Production - Sustaining (HDRTP) team. Our servers and data centers are the foundation upon which our rapidly scaling infrastructure operates efficiently to deliver our innovative services. The HDRTP team is responsible for the end-to-end Hardware Lifecycle of all Meta servers, from exploration and development to production health. HDRTP Engineers work closely with Production Engineering teams, Networking, Hardware Designers, Networking Teams, Manufacturers, Vendors, Datacenter Operation, Capacity, Core Systems and New Product Introduction teams to ensure the smooth operation of systems globally.

Responsibilities

Drive innovation in hardware efficiency by applying expertise in hardware reliability and performance, and translating insights into actionable strategies for hardware reliability and data center optimization Contribute to industry leading research in hardware characterization and fleet/DC efficiency studies across AI platforms, leveraging data-driven and machine learning analytical techniques Conduct in-depth hardware parameter based research and comparative analyses using advanced data analytics and machine learning techniques for failure analysis and diagnosis in production Interface with internal hardware, software engineers and operations teams to understand system architectures and failure modes Proactively create experiments, data analysis and data visualizations to detect and diagnose hardware health issues, focusing on systemic solutions Collaborate on evolving AI platforms, silicon products, thermal and cooling solutions to support the growth of large language models, with a focus on optimizing performance, scalability, and efficiency Develop data frameworks and discover insights to answer relationship between hardware, data center parameters and server failures Develop and implement data-driven strategies using hardware characterization studies to support hardware fleet optimizations and efficiency while supporting improvements to future platform designs Build comprehensive monitoring and predictive frameworks and to make data insights available to partner teams for decision making Collaborate with cross-functional teams to ingest and present data on evolving domains and specialized hardware technologies, components, datacenters Share insights with stakeholders and software teams to develop architectures to handle server failures based on hardware health data Troubleshoot, diagnose and root cause of system failures and isolate the components or failure scenarios with in depth statistical studies while working with stakeholders internally and externally

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of hands-on software/firmware/hardware engineering to build systems/products for the IT industry Troubleshooting and data tooling, including data analysis, building analytical models, and visualizations Knowledge of server architecture and components across Compute/Storage/AI Systems/Networking Experienced in the integration of lab tools for automated workflows Experience with Linux systems and server systems management Master’s degree or PhD in Computer Engineering, Electrical Engineering, or related field Proficient in SQL, Python or C/C++ (data structures, algorithms, and OOP) Experience with some of the following modules/domains: PCIe, Networking, Flash, Memory, CPU, GPU, DRAM (DDR4/5 or HBM)

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