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
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
Minimum Qualifications
• 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
Preferred Qualifications
• 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
