Engineer, AI Battery Simulation

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SES AI Corp. (NYSE: SES) is dedicated to accelerating the world’s energy transition through groundbreaking material discovery and advanced battery management. We are pioneering the integration of cutting‑edge machine learning into battery R&D, and our AI‑enhanced, high‑energy‑density and high‑power‑density Li‑Metal and Li‑ion batteries are the first in the world to utilize electrolyte materials discovered by AI. This powerful combination of “AI for science” and material engineering enables batteries for transportation (land and air), energy storage, robotics, and drones—truly taking us Beyond Li‑ion™.

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• Highly competitive salary and robust benefits, including comprehensive health coverage and attractive equity/stock options in a NYSE‑listed company.
• The opportunity to contribute directly to a meaningful scientific mission: accelerating the global energy transition with clear and broad public impact.
• A dynamic, collaborative environment at the intersection of AI, computational science, and advanced battery technology.
• Significant opportunities for growth as you collaborate with leading experts in AI, R&D, and engineering.

We are seeking an Engineer to architect and lead our AI‑driven molecular simulation and materials informatics platform for next‑generation battery materials.

This leader will bridge advanced AI model architectures with computational chemistry, molecular dynamics (MD), and phase‑field simulation, designing and scaling the scientific computing platforms and tool chains that power SES AI’s materials discovery and battery R&D.

You will support the productization of AI4

Science capabilities—from ML force fields and surrogate models to automated MD workflows—turning them into robust, developer‑friendly APIs and platforms used across SES’s global R&D organization.

• Lead the end‑to‑end design of a scientific computing platform for battery materials, integrating AI/ML models, experimental data, and cloud infrastructure.
• Architect and implement high‑performance computing (HPC) and C++‑based simulation services for large‑scale MD, phase‑field, and related materials models.
• Define and evolve the API architecture and platform interfaces that expose simulation, ML, and data services to internal users and tools.

• Drive development and deployment of AI/ML models for materials informatics, including ML force fields, surrogate models, and uncertainty‑aware prediction pipelines.
• Build and manage MD automation systems and simulation tool chains that scale across thousands of runs, integrating job scheduling, monitoring, and data management.
• Translate research prototypes (e.g., new ML models for materials, dendrite growth algorithms) into reliable, production‑grade services.

• Work closely with battery scientists, electrochemists, and experimentalists to map R&D needs into platform features and workflows.
• Develop simulation and algorithmic capabilities focused on battery dendrite growth, degradation mechanisms, and electrolyte/material performance.
• Ensure tight integration of simulation and AI outputs with experimental workflows, data pipelines, and informatics dashboards.

• C++ and high‑performance/scientific computing
• HPC systems and parallel computing (MPI, CUDA, GPU acceleration, or similar)
• Molecular dynamics (MD) simulation and related tools/workflows
• API engineering and large‑scale platform architecture
• Battery informatics and AI4
  
  Science for materials
• MD workflow automation & simulation toolchain design
• Hybrid expertise in scientific computing + modern software engineering

• PhD in Materials Science, Computational Physics, Computational Chemistry, or a closely related field.
• 1+ years (post‑graduate) of experience in computational materials science, including molecular dynamics and/or phase‑field simulation.
• Proven track record building production‑grade scientific software in C++ and/or similar systems languages, ideally in an HPC context.
• Hands‑on experience with AI/ML for…