Battery Algorithms Engineering Intern

About the Role

At Meta Reality Labs, we explore, innovate, and design hardware for the next generation of AI glasses, wearables, and virtual, augmented, and mixed reality experiences. The battery team develops power sources for these devices. We are seeking a highly motivated Battery Algorithm Intern with a background in battery modeling, state estimation, and controls to join our team. This internship will be 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 (e.g., multi-RC equivalent circuit models) that guide battery design decisions.
• Propose methods for efficient parameter identification from experimental data and validate model accuracy.
• Leverage battery models to estimate battery life and power delivery capability across operating conditions like temperature, state of charge, and aging.
• Develop and validate battery algorithms to improve performance metrics such as charge time, cycle life, and run time.
• Analyze field battery telemetry to assess existing algorithm performance and derive representative use cases for new algorithm development.
• Leverage insights from electrochemistry to propose new modeling and estimation techniques and compare their efficacy.
• Design agentic workflows with human-in-the-loop review to automate repetitive battery engineering tasks (e.g., test data processing, model parameter identification, model validation, field telemetry triage).
• Package battery models, simulations, and analysis scripts as tested, well-documented tools for reproducible use by engineers and AI agents.

Requirements & Tech Stack

• 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, to accelerate research or engineering work.
• Interpersonal skills and experience working effectively in a dynamic, team-oriented environment.

Qualifications

• Currently pursuing a Ph.D. degree in engineering, mechanical engineering, materials science, chemistry, physics, or a related field.
• 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.
• Must obtain work authorization in the country of employment at the time of hire and maintain it throughout employment.
• Intent to return to a full-time degree program after the internship.

Preferred Qualifications

• Experience developing battery management algorithms (e.g., state-of-charge, state-of-health, 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 (e.g., with tool calling, MCP servers, retrieval, or multi-agent orchestration).
• Experience evaluating and safeguarding AI outputs (e.g., designing evaluations, test cases, or quality checks).
• Familiarity with cell/battery testing equipment (Maccor, Arbin, Neware, BioLogic, or equivalent).
• Prior internship or work experience in high-volume consumer electronics.