Manufacturing Operations Engineer - Reality Labs

As a Manufacturing Operations Engineer at Meta, you will play a key hands-on role in managing line operations, ensuring ramp readiness, and driving engineering sustained excellence at our contract manufacturing (CM) partner sites. In this role, you will bridge day-to-day mass production execution with technical process optimizations. You will take ownership of post-launch product manufacturing plans (PMPs), working closely with cross-functional teams to drive line balancing, process/layout optimization, yield bridge maturation, yield tracking automation, and labor efficiency improvements.

Responsibilities

• Support CM factory bring-up and ramp execution. Participate in line bring-up, capacity planning, layout review, and material flow verification to ensure timely product delivery (ExF)
• Track daily CM production metrics, including output, labor allocation, line efficiency, and MES reporting. Identify operational risks early and escalate appropriately to meet operational targets
• Support Engineering Change Orders (ECO/PRQ) executions, line conversions, and equipment cross-qualification at CM facilities to ensure smooth implementation without impacting supply
• Audit FATP and SMT line layouts post-launch, driving cycle time (CT) reduction, bottleneck elimination, and labor optimization
• Drive Overall Equipment Effectiveness (OEE) improvements, test cycle reduction, and retest rate minimization
• Maintain the functional yield bridge (FPY/LPY). Actively participate in Major Issue List (MIL) and technical issue forums (PIL/TIL), conducting deep-dive failure analysis and corrective actions (FACA) for process drift or yield drops
• Utilize data analysis tools (Python, JMP, Tableau) to build automated yield tracking dashboards, streamline daily reporting workflows, and speed up FACA root-cause identification

Minimum qualifications

• 3+ years of hands-on experience in high-volume electronics manufacturing, specializing in manufacturing operations, sustaining process engineering, or hardware operations
• Solid technical understanding of FATP and SMT assembly/test processes, including yield analysis, cycle time reduction, and OEE optimization
• Hands-on experience with data analytics or scripting tools (Python, JMP, Tableau, or modern AI tools) for yield tracking, data visualization, and root-cause analysis
• Strong execution mindset with a proven ability to prioritize tasks, troubleshoot technical issues independently, and operate effectively in a fast-paced environment
• Effective communication and interpersonal skills to collaborate and hold CM partners and internal cross-functional teams accountable
• Ability to travel frequently across APAC and other global locations as needed Solid understanding of lean manufacturing methodologies and Smart Factory/MES systems
• Direct experience with automated line bring-up, tester qualification, or process automation projects
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience with CM factory transfers, line conversions, or cross-regional qualifications
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

Preferred qualifications

• Solid understanding of lean manufacturing methodologies and Smart Factory/MES systems
• Direct experience with automated line bring-up, tester qualification, or process automation projects
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience with CM factory transfers, line conversions, or cross-regional qualifications
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)