Battery Modeling Engineer

Base Power Company • Austin, TX

6d • Onsite

About The Position

Base is hiring a Battery Modeling Engineer to build the data and degradation models that explain how its deployed batteries age in real-world conditions. The role combines software engineering, data science, and battery science, using fleet telemetry and cell-level testing data to create trusted datasets and models that predict capacity fade, resistance growth, and remaining useful life.

The engineer will own degradation analytics end to end, from data pipelines and models to semi-empirical degradation tools used across Base. The role also includes helping establish Base’s cell characterization lab and developing processes that generate reliable aging data. The resulting models and insights will support fleet operations and long-term performance planning.

Base describes itself as a startup where priorities can shift quickly and responsibilities may evolve with business needs. The company works in person and describes its pace as intense and all-in.

Requirements

• Background in chemistry, battery physics, or a related field such as electrochemistry, materials science, or chemical engineering.
• Hands-on experience with battery modeling, ideally semi-empirical or physics-informed degradation models for lithium-ion cells.
• Proficiency in Python and SQL, or equivalent software and data skills.
• Familiarity with cell testing and characterization, such as cycling, HPPC, EIS, or similar.
• A strong ownership mindset, with a focus on outcomes rather than only assigned tasks.

Nice To Haves

• PhD in physics modeling or battery chemistry.
• Experience with field or fleet data from deployed energy storage, EVs, or consumer electronics.

Responsibilities

• Build and validate semi-empirical degradation models for calendar and cycle aging, capacity fade, and resistance growth.
• Help found and set up Base’s cell characterization lab by defining test plans, selecting equipment, and establishing processes for reliable aging data.
• Analyze fleet- and device-level data to understand how temperature, state of charge, and usage patterns affect degradation, and validate model predictions against real-world behavior.
• Translate model outputs into tools and insights that engineering, fleet, and markets teams can use to make battery-operation decisions.
• Write production-quality Python and SQL, or equivalent, with tests, documentation, and monitoring to maintain model trustworthiness as the fleet grows and ages.
• Track model history and communicate model changes across the organization.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed