Listing evidence and provenance
- Source
- Greenhouse View original listing
- Freshness
- Open in the current public read path; this is not an employer guarantee.Last observed November 1, 2026
- Classification
- Modern power-system classification not yet published for this listing.Legacy source industry field: Energy Storage
- Pay provenance
- Employer-provided pay
Job Description
The SES AI Prometheus team is seeking an exceptional Computational Materials Scientist to combine physics-based simulation (DFT, MD, quantum modeling) with AI-assisted material prediction to generate high-quality training data and accelerate materials discovery.
Key Responsibilities
- Atomistic Modeling & Simulation
- Conduct and oversee DFT (Density Functional Theory), MD (Molecular Dynamics), and QM (Quantum Mechanics) simulations of battery components, including electrolytes, coatings, and electrodes.
- Develop and refine ML-enhanced force fields and surrogate models to accelerate simulation time scales and enable multi-scale simulation efforts.
- Apply expertise in atomistic simulation and quantum modeling to solve key challenges in electrochemical energy materials (e.g., batteries/fuel cells).
- AI Data Generation & Prediction
- Generate high-quality, structured simulation data to serve as training sets for AI property prediction models and material screening modules.
- Contribute to the development of battery domain LLM features and advanced property-prediction models.
- Automate complex simulation workflows using strong coding practices to enhance efficiency and scalability.
- Collaboration & Tooling
- Collaborate with experimental teams, leveraging a hybrid computational + experimental literacy to validate models and drive design iteration.
- Utilize advanced simulation tools (VASP, Quantum Espresso) and data science libraries (TensorFlow, Pandas) to manage and analyze large datasets.
Requirements
- LLM Development: Experience in developing battery domain LLM features or property-prediction models.
- Hybrid Skillset: Demonstrated experience working in a hybrid computational + experimental environment.
- Tooling Diversity: Familiarity with additional data analysis tools like R, SQL, MATLAB, and time-series forecasting libraries like Prophet.
- Target Background: Previous experience at national laboratories, XtalPi, Entalpic, or deep battery modeling groups.
- The salary range for this position as required under applicable pay transparency laws.
- Salary Range
- $180,000
- —
- $200,000 USD
Benefits & Perks
- A highly competitive salary and robust benefits package, including comprehensive health coverage and an attractive equity/stock options program within our NYSE-listed company.
- The opportunity to contribute directly to a meaningful scientific project—accelerating the global energy transition—with a clear and broad public impact.
- Work in a dynamic, collaborative, and innovative environment at the intersection of AI and material science, driving the next generation of battery technology.
- Significant opportunities for professional growth and career development as you work alongside leading experts in AI, R&D, and engineering.
- Access to state-of-the-art facilities and proprietary technologies are used to discover and deploy AI-enhanced battery solutions.
Ready to Apply?
Apply directly on SES's site
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