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Salary
≈ $236k – $450k per year (Estimated)
Location
In office (Redmond)
Seniority
Staff · 8+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 12, 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.
As a Manufacturing Engineer in Reality Labs Research, you will develop novel manufacturing processes - spanning research-stage components and materials through complex, fully integrated devices - and advance them from early feasibility and proof-of-concept through process qualification and pilot production, delivering reliable, high-performing hardware prototypes. The development of state-of-the-art prototypes will require the intersection of novel materials, manufacturing processes, mechanical, electrical, and software fields. You will bring experience with a wide variety of manufacturing processes and demonstrated experience of leading cross-functional engineering efforts to rapidly develop and scale technologies from low to high volumes. More broadly, you will work with a diverse and highly interdisciplinary team of researchers and engineers and will have access to cutting edge technology, resources, and testing facilities.

Responsibilities

Lead manufacturing development activities across cross-functional teams to deliver reliable, high-performing hardware prototypes Provide design-for-manufacturability, assembly, and test feedback to research scientists and engineers to improve the manufacturing feasibility of novel technologies Set manufacturing technical direction across multiple concurrent research programs, defining and executing the process maturation path that scales state-of-the-art components and prototypes from early feasibility to pilot-production volumes Grow in-house manufacturing capabilities and manage external manufacturing partnerships Raise the bar for manufacturing excellence and best practices by developing, and continuously improving, processes and relationships which empower researchers and design engineers to build increasingly complex systems

Qualifications

Bachelor's degree in Manufacturing Engineering, Process Engineering, Mechanical Engineering, other relevant field, or equivalent experience 8+ years of experience scaling hardware technologies from early-stage feasibility to pilot-production or mass manufacture Experience developing high-volume consumer products with stringent size, weight, power, and cost constraints in wearables, robotics, or similar Experience designing and implementing process development plans, design of experiments (DOE), critical process parameters, and quality control strategies Experience defining hardware build and supply chain plans, and managing external manufacturing vendors to meet program schedule and quality requirements Experience with any combination of manufacturing techniques, such as electro-mechanical integration, coatings, laminating, active optical alignment, molding, machining, additive manufacturing, and adhesive bonding Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Master's degree in Manufacturing Engineering, Process Engineering, Mechanical Engineering, or other relevant field Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience establishing in-house prototyping or pilot-line capability, including equipment selection, installation, process qualification, and capacity planning Experience developing processes for novel or unproven materials, including material characterization and process-window definition Experience with CAD, such as NX or related programs Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

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