Senior Computational Materials Scientist

At SES AI, base pay is one part of our total compensation package and is determined within a range. The base pay range for this role is between $150,000 and $250,000. SES AI considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate’s work experience, location, education/training, and skills.

What We Offer

Company paid Health and Dental insurance (ability to add dependents)
Global travel insurance for employees traveling while on business
Company sponsored retirement plan with 100% vesting and up to 5% match.
Life and AD&D Insurance
Employee Assistance Program 
Six Paid Holidays, and one floating holiday per a quarter equivalent to 4 per calendar year
10 accrued vacation days per calendar year that increases with tenure.
Bonus + Equity, based on position and eligibility requirements

Note: SES AI benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. 

About SES AI Corp.

SES AI Corp. (NYSE: SES) is powering the future of global electric transportation—on land and in the air—with the world’s most advanced Li-Metal batteries. As the first battery company to fully integrate superintelligent AI into its workflow, SES AI accelerates innovation across R&D, materials sourcing, cell design, manufacturing, and battery health and safety monitoring. With headquarters in Boston and operations in Singapore, Shanghai, and Seoul, SES AI is redefining how batteries are discovered, designed, and deployed.

About the Prometheus Team

The Prometheus team is SES AI’s AI research and development division. We are an interdisciplinary team of computational materials scientists, software engineers, and machine learning researchers working side-by-side with experimental chemists and battery engineers. Together, we drive rapid innovation in battery materials by building intelligent, automated, and scalable scientific tools.

About Molecular Universe (MU)

Molecular Universe (MU) is SES AI’s flagship product for AI-accelerated materials discovery. MU-0, our first release, maps over 10^8 small molecules across various key properties predicted by quantum chemistry, AI/ML, and experimental data. Built with GPU-accelerated simulation, high-throughput automation, and advanced visualization, it empowers researchers to explore the vast molecular landscape with ease.

About the Role

We’re seeking a Senior Computational Materials Scientist to join the development of the Molecular Universe and participate in simulation efforts related to solid electrolyte interphase (SEI) modeling, chemical reaction simulation, force field development, and molecular dynamics acceleration on large-scale HPC systems.

You’ll collaborate with other computational materials scientists, AI engineers, software developers, and experimental teams to build tools that bridge quantum chemistry, statistical mechanics, and machine learning for real-world molecular discovery.

Key Responsibilities

• Design and run large-scale quantum chemistry and molecular dynamics simulations (e.g., GPU4PySCF, GROMACS, LAMMPS, Gaussian).

• Develop or refine interatomic potentials/force fields tailored to electrolyte systems.

• Develop, implement, and refine tooling to investigate SEI formation, including chemical reaction network pipelines and atomistic simulations.

• Contribute to property calculation workflows for quantum descriptors (HOMO, LUMO, ESP), thermodynamics, and kinetics.

• Automate high-throughput simulations with Python, HPC schedulers (e.g., SLURM), and distributed computing.

• Integrate new simulation capabilities into our Molecular Universe platform via APIs or modular Python packages.

Qualifications

Required:

• PhD in Materials Science, Chemistry, Chemical Engineering, Physics, or related field.

• 5+ years of post-PhD experience in computational chemistry/materials (academic or industry).

• Hands-on expertise with molecular simulation tools such as GROMACS, LAMMPS, Gaussian, VASP, Quantum Expresso, ADF, GPU4PySCF, or equivalent.

• Strong coding skills in Python, including scientific stack (NumPy, ASE, PySCF, etc.), and experience with developing research-grade code.

• Familiarity with high-throughput computation and large-scale data analysis on HPC or GPU clusters.

• Strong communication skills and ability to work cross-functionally with experimental and AI teams.

Preferred Experience:

• Experience with battery materials, solid/liquid interfaces, or electrolyte development.

• Prior work on force field parameterization, reactive MD (Polarizable FF, ReaxFF, MLFF), or coarse-grained methods.

• Familiarity with cheminformatics concepts, including molecular representations (SMILES strings, fingerprints, etc.) and chemical space traversal.

• Contributions to open-source tools or published methods in molecular simulation or AI/ML

• Familiarity with unsupervised machine learning, including dimensionality reduction techniques and clustering algorithms beyond k-means.

• Experience with CUDA programming

Who Will Thrive in This Role

• You enjoy solving hard, interdisciplinary problems at the boundary of theory and application.

• You will push the boundaries of capabilities provided by common computation tools

• You’re a self-starter with a deep curiosity for molecules, batteries, and computational design.

• You can prototype fast, scale up intelligently, and care deeply about reproducible science.

• You love the idea of building something novel—from raw simulation data to interactive platforms used by researchers worldwide.