Production Systems Engineer, NPI AI

Meta; Austin (TX); On-site; USD 144,000 - 204,000; Full time

Job summary

Meta is seeking a Hardware Engineer to support validation and production readiness of AI and HPC infrastructure across Meta's data centers.

You will work at the intersection of AI silicon, server systems, and data center operations, partnering with hardware design, firmware, software, and capacity engineering teams to bring AI accelerators and GPU-based platforms from new product introduction through full-scale deployment.

Qualifications

• 6+ years of experience in hardware engineering focusing on AI servers, GPUs, AI accelerators, or HPC in a data center.
• 6+ years of experience in hardware validation, system bring-up, or NPI for AI/HPC platforms.
• Experience debugging hardware failures across power delivery, thermal management, signal integrity, or high-speed interconnects like PCIe, NVLink, or HBM in AI systems.
• Experience developing test specifications, qualification procedures, and failure analysis documentation for AI/HPC hardware.
• Experience collaborating with silicon vendors, ODMs, or contract manufacturers to resolve hardware quality and reliability issues for AI infrastructure.

Responsibilities

• Lead hardware system validation and qualification for AI server platforms, GPU clusters, and AI accelerator systems entering production data center environments.
• Drive new product introduction efforts for AI/HPC hardware by defining acceptance criteria and coordinating cross-functional readiness reviews.
• Develop and execute test plans covering thermal, power, and electrical characterization of AI server systems at component, board, and rack levels.
• Investigate and root-cause complex hardware failures across the full stack including silicon, firmware, and subsystem components.
• Collaborate with AI silicon vendors and ODMs to resolve hardware issues and ensure production quality standards are met.
• Define and improve hardware qualification methodologies and failure analysis processes for scaling across large fleet deployments.
• Partner across teams to support hardware deployment planning, rack integration, and production ramp for GPU and AI accelerator systems.
• Analyze fleet telemetry and failure data to identify systemic reliability risks and drive corrective actions.
• Contribute to AI hardware design reviews and provide feedback on system architecture and manufacturability.
• Communicate hardware qualification status and readiness for deployment to cross-functional stakeholders and leadership.

Skills

AI servers

GPUs

AI accelerators

HPC systems

data center

Job description

Summary:

Meta is seeking a Hardware Engineer to support the validation and production readiness of AI and high-performance computing infrastructure deployed across Meta's global data centers. In this role, you will work at the intersection of AI silicon, server systems, and data center operations, partnering with hardware design, firmware, software, and capacity engineering teams to bring AI accelerators and GPU-based server platforms from new product introduction through full-scale deployment. Your work will directly influence the reliability, scalability, and performance of the AI infrastructure that powers Meta's machine learning and AI initiatives.

Required Skills:

Production Systems Engineer, NPI AI Responsibilities:

1. Lead hardware system validation and qualification activities for AI server platforms, GPU clusters, and AI accelerator systems entering Meta's production data center environment

2. Drive new product introduction efforts for AI/HPC hardware by defining acceptance criteria, coordinating bring-up activities, and managing cross-functional readiness reviews with silicon, firmware, and software teams

3. Develop and execute test plans covering thermal, power, and electrical characterization of AI server systems at component, board, and rack levels

4. Investigate and root-cause complex hardware failures across the full stack, including AI silicon, firmware, system software, and thermal subsystems

5. Collaborate with AI silicon vendors and original design manufacturers to resolve hardware issues, drive engineering change orders, and ensure production quality standards are met

6. Define and improve hardware qualification methodologies and failure analysis processes for AI/HPC platforms to scale across large fleet deployments

7. Partner with AI platform and capacity engineering teams to support hardware deployment planning, rack integration, and production ramp execution for GPU and AI accelerator systems

8. Analyze fleet telemetry, failure rate data, and field return trends to identify systemic reliability risks in AI infrastructure and drive corrective actions

9. Contribute to AI hardware design reviews and provide feedback on system architecture, component selection, and manufacturability to improve production outcomes

10. Communicate hardware qualification status, risk assessments, and deployment readiness for AI/HPC systems to cross-functional stakeholders and engineering leadership

Minimum Qualifications:

Minimum Qualifications:

1. 6+ years of experience in hardware engineering with a focus on AI servers, GPUs, AI accelerators, or high-performance computing systems in a data center environment
2. 6+ years of experience in hardware validation, system bring-up, or new product introduction for AI/HPC platforms
3. Experience debugging hardware failures across multiple domains including power delivery, thermal management, signal integrity, or high-speed interconnects such as PCIe, NVLink, or HBM in AI systems
4. Experience developing test specifications, qualification procedures, and failure analysis documentation for AI/HPC hardware systems
5. Experience collaborating with silicon vendors, original design manufacturers, or contract manufacturers to resolve hardware quality and reliability issues for AI infrastructure

Preferred Qualifications:

Preferred Qualifications:

1. Experience with scripting or automation for hardware test workflows, data collection, and failure triage in a Linux-based environment
2. Familiarity with hardware telemetry frameworks, out-of-band management protocols such as IPMI or Redfish, and fleet-level diagnostics tooling for AI infrastructure
3. Experience with AI/HPC hardware platforms including GPU clusters, AI accelerators, or custom AI server designs at rack or pod scale
4. Knowledge of high-speed interconnect standards such as PCIe Gen 4/5, NVLink, CXL, or high-bandwidth memory in the context of AI/HPC system validation

Public Compensation:

$144,000/year to $204,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [e-mail].