Battery Algorithms Engineering Intern

About the Role

At Meta Reality Labs, our goal is to explore, innovate, and design the hardware for the next generation of AI glasses, wearables, and virtual, augmented, and mixed reality experiences. The mission of the battery team is to develop power sources for the devices that enable these experiences. We are looking for a highly motivated Battery Algorithm Intern with a background in battery modeling, state estimation, and controls to join our team. Our internships are twelve (12) to twenty four (24) weeks long with various start dates throughout the year.

Key Responsibilities

• Collaborate with cell, algorithm, and validation engineers to develop and validate battery models, such as multi-RC equivalent circuit models, that guide battery design decisions.
• Propose methods to identify model parameters quickly and efficiently from experimental data, and validate model accuracy.
• Leverage battery models to estimate battery life and power delivery capability across operating conditions such as temperature, state of charge, and aging.
• Develop and validate battery algorithms that improve performance metrics such as charge time, cycle life, and run time.
• Analyze field battery telemetry to assess the performance of existing algorithms and derive representative use cases that guide the development of new ones.
• Leverage insights from electrochemistry to propose new modeling and estimation techniques, and compare their efficacy.
• Design agentic workflows, with human-in-the-loop review, that automate repetitive battery engineering tasks such as test data processing, model parameter identification, model validation, and field telemetry triage.
• Package battery models, simulations, and analysis scripts as tested, well-documented tools that both engineers and AI agents can use reproducibly.

Requirements & Tech Stack

• Knowledge of Li-ion battery technology, including electrochemistry, electrical characteristics, and battery testing.
• Experience with equivalent circuit modeling of Li-ion cells, including parameter estimation.
• Knowledge of control and estimation theory and its application to Li-ion battery modeling.
• Proficiency with scripting, data processing, and dynamic simulation in MATLAB and/or Python.
• Hands-on experience using AI tools, such as LLM-based coding assistants or agents, as collaborators to accelerate research or engineering work.
• Interpersonal skills and experience working effectively in a dynamic, team-oriented environment.
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
• Intent to return to full-time degree program after completion of the internship.

Preferred Qualifications

• Experience developing battery management algorithms, such as state-of-charge, state-of-health, or charging algorithms.
• Experience developing test plans to validate algorithms for battery management systems.
• Working knowledge of battery fuel gauge algorithms used in consumer electronics.
• Experience with embedded programming in C/C++, unit testing, and firmware integration.
• Knowledge of model order reduction, efficient optimization methods, and adaptive control techniques for real-time battery management on memory-constrained ICs.
• Experience applying data-driven or physics-informed AI/ML methods to battery modeling, control, and health diagnostics.
• Experience designing AI agents and agentic workflows.
• Experience evaluating and safeguarding AI outputs.
• Familiarity with cell/battery testing equipment (Maccor, Arbin, Neware, BioLogic, or equivalent).
• Prior internship or work experience in high-volume consumer electronics.