AI Transformation Lead, Hardware Engineering

Meta Meta · Big Tech · Sunnyvale, CA +2 · Remote

This role leads the AI transformation within hardware engineering for consumer electronics (wearables, AR/VR). It involves defining roadmaps, deploying ML/GenAI into design, simulation, and manufacturing workflows, and bridging the gap between AI research and practical hardware applications. The focus is on accelerating hardware development cycles and improving engineering outcomes through AI integration.

What you'd actually do

  1. 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
  2. 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
  3. 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
  4. 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
  5. Communicate AI transformation strategy, progress, and trade-offs to hardware engineering leadership and executive stakeholders through structured written and verbal briefings

Skills

Required

  • Hardware systems engineering
  • Systems architecture
  • Technical program management for consumer electronics
  • Leading large-scale technical transformation programs
  • Applying AI, machine learning, or data-driven methodologies to hardware engineering workflows
  • Defining strategic roadmaps
  • Driving organizational alignment
  • Communicating complex technical strategy
  • Deploying generative AI or large language model-based tools within engineering design or verification workflows
  • Building or scaling AI-enabled design space exploration, predictive failure analysis, or simulation acceleration capabilities

Nice to have

  • Experience with hardware development processes for wearable devices
  • Establishing new engineering practices or centers of excellence

What the JD emphasized

  • AI transformation roadmap
  • AI-driven tools and methodologies
  • machine learning and generative AI capabilities
  • AI transformation initiatives
  • state-of-the-art AI capabilities
  • AI transformation strategy
  • AI-augmented hardware engineering programs
  • AI fluency
  • AI integration challenges
  • AI, machine learning, or data-driven methodologies
  • generative AI or large language model-based tools
  • AI-enabled design space exploration

Other signals

  • AI transformation roadmap for hardware engineering
  • Deploying machine learning and generative AI capabilities into hardware engineering workflows
  • Applying AI, machine learning, or data-driven methodologies to hardware engineering workflows
  • Deploying generative AI or large language model-based tools within engineering design or verification workflows
  • Building or scaling AI-enabled design space exploration, predictive failure analysis, or simulation acceleration capabilities