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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
$173,000/year to $245,000/year + bonus + equity + benefits
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