Job description

Meta Reality Labs is seeking a Battery Algorithm Engineer to define and lead the development of advanced battery management algorithms and state estimation systems for next-generation virtual and augmented reality devices, including headsets, wearables, and smart glasses. In this role, you will own the long-term technical strategy for battery algorithms across Meta's Reality Labs hardware portfolio, driving innovations in state-of-charge estimation, state-of-health prediction, cell balancing, and adaptive charging to maximize energy density, safety, and longevity in highly constrained wearable form factors. Responsibilities Lead the design and development of battery algorithms across the wearables portfolio — SOC/SOH estimation, fuel gauging, charge-time and peak-power optimization, and battery-life extension Shape the technical strategy and roadmap for battery algorithms, contributing to key architectural decisions and the standards and best practices that the team builds on Drive cross-functional execution across cell, hardware, firmware, and validation teams, data science, data engineering, resolving challenging algorithm problems and unblocking programs to deliver on schedule Own algorithm requirements and configurations for fuel gauge ICs and drive their integration to silicon across NPI programs Advance control theory and data-driven AI-ML methods to improve estimation accuracy and robustness across temperature, aging, and load Ground algorithm design in the underlying battery electrochemistry — leverage physics-based and reduced-order battery models to inform SOC/SOH estimation, charge optimization, and degradation-aware control Turn field telemetry and degradation behavior into algorithm improvements — attribute real-world fade to its drivers and feed it back into the next generation of estimation and charge-control algorithms Mentor and grow engineers, raise the technical bar, and help influence engineering direction across the team 8+ years of experience developing battery management system algorithms, including state estimation, adaptive charging, or cell balancing for consumer electronics or wearable devices Experience with electrochemical modeling techniques such as equivalent circuit models, physics-based models, or data-driven approaches applied to lithium-ion or emerging cell chemistries Experience implementing and validating battery algorithms in embedded firmware environments, including integration with battery management system ICs and real-time operating system constraints Experience leading cross-functional technical programs involving hardware, firmware, and electrochemistry teams from algorithm definition through product validation Experience communicating complex algorithm design decisions and technical trade-offs in writing to both engineering and non-engineering stakeholders Experience with data-driven AI/ML algorithms for battery control and health diagnostics Working knowledge of communication protocols such as SPI and I2C, and interfacing with microcontroller peripherals Background in high-volume consumer electronics or electric vehicle battery applications Experience developing embedded applications for microprocessors, including familiarity with real-time operating systems Understanding of hardware and clock-level considerations (interrupts, delays, clock gating, polling) PhD in electrical engineering, electrochemistry, or a relevant field, with 8+ years of experience in developing battery algorithms Working-level experience with Li-ion degradation mechanisms (capacity/power fade, swell) and how they inform SOH and charge-optimization algorithms

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Keywords to mirror

aiml

Platform: meta
Effort: medium