AI Transformation Lead, Hardware Engineering

Define and own the multi-year AI transformation roadmap for hardware engineering, identifying opportunities to embed AI-driven tools and methodologies across design, simulation, verification, and manufacturing workflows.

Lead cross-functional programs that deploy machine learning and generative AI capabilities into hardware engineering workflows, including design space exploration, failure mode analysis, and predictive validation.

Establish frameworks for evaluating and prioritizing AI transformation initiatives based on engineering impact, feasibility, and alignment with hardware product roadmaps for wearables and AR/VR devices.

Collaborate with research and applied AI teams to translate state-of-the-art AI capabilities into practical hardware engineering applications, bridging the gap between research prototypes and production-ready tooling.

Communicate AI transformation strategy, progress, and trade-offs to hardware engineering leadership and executive stakeholders through structured written and verbal briefings.

Define success metrics and evaluation criteria for AI-augmented hardware engineering programs, and drive accountability across partner teams to deliver measurable improvements.

Identify organizational capability gaps and develop enablement strategies to build AI fluency across hardware engineering teams, including tooling adoption, workflow integration, and change management.

Engage with external technology partners, vendors, and the broader hardware AI ecosystem to inform Meta's transformation strategy and identify emerging capabilities relevant to consumer electronics development.

Provide technical and strategic guidance to engineering leaders and program teams navigating ambiguous, first-of-a-kind AI integration challenges in hardware development contexts.

12+ years of experience in hardware systems engineering, systems architecture, or technical program management for consumer electronics, wearable devices, wearables hardware, or related hardware product domains.

Experience leading large-scale technical transformation programs that span multiple engineering disciplines and organizational boundaries within a hardware development environment.

Experience applying AI, machine learning, or data-driven methodologies to hardware engineering workflows such as design automation, simulation, test and validation, or manufacturing process optimization.

Experience defining strategic roadmaps and driving organizational alignment across hardware engineering, research, and product leadership at the executive level.

Experience communicating complex technical strategy and cross-functional program trade-offs in writing to both engineering and non-technical executive audiences.

Experience deploying generative AI or large language model-based tools within engineering design or verification workflows for consumer hardware products.

Experience building or scaling AI-enabled design space exploration, predictive failure analysis, or simulation acceleration capabilities in a hardware engineering context.

Familiarity with hardware development processes for wearable devices, including subsystem integration, bring-up, and mass production readiness.

Track record of establishing new engineering practices or centers of excellence that measurably improved development velocity or product quality across a hardware organization.