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Be part of building new, innovative hardware that redefines the way people work, play, and connect! As a Capex Product Cost Engineer at Meta Reality Labs, you will own the financial health of the capital equipment investment behind the AR Glasses portfolio — from early process concept and line architecture through ramp. Capital is one of the largest and least reversible commitments in a hardware program: decisions made at process definition lock in tooling, automation, and test capacity for years. You will team up cross-functionally with Product Operations, Strategic Sourcing, Hardware engineering, Tooling Engineering, Manufacturing Design Engineering, Design for Manufacturing/Test, Test Engineering and other cross-functional teams to set capex targets, drive the capital budget, and build the intergenerational re-use strategy that compounds savings across the portfolio. You'll influence process and product architecture through trade-off analysis — cycle time vs. capital, automation vs. labor, dedicated vs. portfolio re-use.

Qualifications:

BS or higher in Manufacturing & Operations, Industrial, Mechanical or Electrical Engineering, or equivalent experience 8+ years of experience in capital cost management, manufacturing/process engineering, tooling, or automation roles in hardware products Experience building capital or capacity models (equipment cost, UPH, cycle time, OEE, utilization, staffing) to support investment decisions Knowledge of Operations and Supply Chain with demonstrated effective communication skills Experience collaborating with stakeholders across engineering, sourcing, and finance functions to align on trade-offs between cost, schedule, and technical requirements Experience applying analytical and problem-solving methods to cost, capital, or supply chain challenges and communicating findings to cross-functional stakeholders Experience with equipment re-use, redeployment, or intergenerational tooling strategy across product generations Familiarity with capital governance, depreciation, payback/NPV analysis, and asset disposition Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience with complex capital equipment - including new line bring-up and ramp Master's degree or MBA in a relevant field (e.g., Engineering, Operations, Business) 10+ years of experience in capital cost, manufacturing engineering, or product cost management roles in hardware technology products Background in Manufacturing, Operations or Engineering