USD per year
Battery Modeling Engineer
Onsite (San Francisco, CA) Full-time View all jobs
About Ohm
Cursor and Claude Code reimagined how software products are developed. Our mission is to address the next frontier: artificial intelligence that reimagines how physical products are developed. Every complex physical product - a battery cell, an electric vehicle, a wearables device - is developed through a process that generates enormous quantities of data, almost none of which is used to its potential. This is an opportunity that AI was built to solve. Ohm is an enterprise AI platform that helps engineering teams transform how they develop, test, and validate physical products. Battery teams use Ohm to compress product iteration cycles, cut testing and validation costs, and accelerate data analysis. We are seeking exceptional, high-agency scientists, engineers and operators to join our mission to reimagine how products are built in the next decade.
The opportunity
Your role is to develop and ship the battery models that will deliver the greatest measurable ROI for Ohm's customers. You will use AI tools to operate independently without a traditional R&D-to-engineering handoff. You bring the domain knowledge to identify what to build, the engineering capability to build it, and the commercial instinct to prioritize the changes that compound customer value fastest. You will work directly with the Head of Engineering, and the battery scientists at Ohm's customer accounts. You will write code, deploy models, and own the scientific validity of production systems.
What you will do
- Build and own the models at the core of Ohm's platform - deployed in live customer pipelines where their output drives real engineering decisions.
- Work directly with customers to understand their hardest technical challenges and then develop platform capabilities that close the gap.
- Build the domain knowledge infrastructure that makes Ohm's agentic analysis scientifically credible at the level of the most technically demanding customers.
- Bring frontier battery modelling into the platform before customers ask for it, translated into production capabilities with measurable customer impact.
What we are looking for
- Deep battery expertise. PhD or equivalent depth in battery science, electrochemistry, or a closely related field.
- Modeling fluency. You are strong in both physics-based and data-driven modelling. You have built and validated physics-based battery models in PyBaMM, and you are fluent in data-driven methods: classical machine learning frameworks, Bayesian methods and Gaussian processes. You have built architectures where the two are combined, you understand the trade-offs between them, and you have a strong intuition for which problems require which approach.
- Production code mindset. You write code that runs in production. Python fluency is essential. You hold yourself to the standard that your models are correct when a customer makes a decision based on them.
- AI-native. You use AI coding tools as your primary workflow. You have thought carefully about where AI can accelerate scientific modelling work and can give examples of how you are using AI to do so.
- Original thinker. You have a point of view on where the field's standard approaches to battery modelling are incomplete and the optimal ways to use modelling in the battery development process.
- Energized by delivery of customer value. You want to build models for the battery teams whose decisions depend on your models. Their commercial challenges are the primary signal for what to build next. Their trust in your outputs is the primary measure of whether you have succeeded.