Signal Integrity​/Power Integrity Engineer - Wearables

Position: Signal Integrity / Power Integrity Engineer - Wearables
Signal Integrity and Power Integrity (SIPI) Engineers at Meta design, analyze, and validate SIPI aspects of electrical systems for next-generation hardware products and platforms. They collaborate with multidisciplinary teams and external partners to deliver robust, high-performance solutions from concept through deployment, ensuring Meta’s hardware meets the highest standards for performance, reliability, and electromagnetic compatibility across both product and infrastructure domains.

You will architect and drive SIPI technical strategy across multiple projects and teams, influence system architecture and organizational direction, and serve as a recognized technical leader and mentor for complex, high-impact hardware initiatives.

Signal Integrity / Power Integrity Engineer - Wearables Responsibilities:

Architect and lead system-level Signal Integrity Power Integrity design, simulation, and validation for advanced hardware products, including pre-layout and post-layout analysis of high-speed interfaces and power distribution networks (PDN)
Develop, implement, and continuously improve SIPI methodologies, standards, and guidelines for design, simulation, and validation

Drive SIPI technical strategy and influence system architecture, design trade-offs, and manufacturing processes across multiple projects and teams

Lead cross-functional collaboration with electrical, silicon, packaging, PCB layout, firmware, mechanical, software, manufacturing, and external partners to deliver integrated solutions

Guide vendors and suppliers in developing and validating high-speed signaling solutions, including interconnects, substrates, and compliance testing

Own SIPI validation strategy, including advanced engineering test plans, lab measurements, and compliance for high-speed interfaces (e.g., PCIe, DDR, MIPI, USB, Ethernet, etc.)Troubleshoot and resolve complex SIPI-related design issues using simulation and lab datadrive failure analysis, root cause investigations, and design of experiments

Mentor and develop engineers, foster knowledge sharing, and contribute to organizational initiatives and process improvements

Communicate technical findings, recommendations, and reports clearly to cross-functional stakeholders and leadership

Stay current with industry trends, emerging technologies, and best practices in SIPI, and proactively assess and integrate new approaches to maintain Meta’s leadership in hardware engineering

Minimum Qualifications:

Bachelor's or Master’s degree in Electrical Engineering, or relevant technical field, and/or equivalent practical experience8+ years of experience in SIPI simulation, measurement, or electrical design or a relevant technical field

Experience delivering electrical products, subsystems, or research prototypes from concept through validation, and into high-volume manufacturing, large-scale deployment, or successful technology transfer to product teams

Advanced knowledge of SIPI fundamentals, including impedance control, transmission line theory, PDN characterization, and/or electromagnetic compatibility

Expertise with industry-standard SIPI simulation and modeling tools (e.g., Cadence Sigrity, Ansys SIwave, Keysight ADS, HFSS, Hyperlynx, CST Microwave Studio, HSPICE, or similar)

Experience with advanced lab equipment for SIPI validation (e.g., TDR, VNA, high-speed oscilloscopes, spectrum analyzers, compliance test fixtures, or similar)

Experience with PCB and/or flex design and manufacturing processes, or similar technology

Experience with high-speed electrical interfaces (e.g., DDR, PCIe, MIPI, USB, Ethernet, or similar)
Effective communication and collaboration skills for cross-functional teamwork and/or external partner engagement

Preferred Qualifications:

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Ma…