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:
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. SES AI is the first battery company in the world to accelerate its pace of innovation by utilizing superintelligent AI across the spectrum of its business, from research and development; materials sourcing; cell design; engineering and manufacturing; to battery health and safety monitoring. Founded in 2012, SES AI is an Li-Metal battery developer and manufacturer headquartered in Boston and with operations in Singapore, Shanghai, and Seoul.

Learn more at SES.AI.

About the Role:
The SES AI Prometheus team (AI Research) is seeking versatile Scientific Software Developers to enhance our computational and machine learning simulation workflows. This role involves developing, optimizing, and deploying molecular simulation packages and ML models across high-performance computing (HPC) and cloud environments. You’ll work in close partnership with materials scientists to streamline density functional theory (DFT) calculations, molecular dynamic (MD) simulations, manage complex orchestration tasks, and ensure reproducibility and scalability of our software solutions.

This is a remote position.

Key Responsibilities:

• Code Development and Optimization: Develop, optimize, and maintain custom scripts or computational packages (e.g., in Python, Fortran, C++) to streamline molecular simulations and deploy AI models effectively. Identify and resolve computational bottlenecks for faster and more accurate simulations.
• Software Deployment: Design and implement optimized workflows for the deployment of molecular simulation packages across high-performance computing (HPC) environments and cloud platforms. Ensure scalability and reliability of developed packages.
• Cross-functional Collaboration: Partner closely with scientists, engineers, and AI specialists, contributing to interdisciplinary projects and translating research requirements into efficient computational solutions.
• Documentation and Reproducibility: Maintain rigorous documentation standards for code, models, and deployment workflows, ensuring reproducibility and compliance with industry standards.
• Mentorship and Documentation: Mentor scientists on best practices in software engineering, maintain rigorous documentation for code and deployment workflows, and uphold industry standards for reproducibility and compliance.

Qualifications:

• Experiences: +3 years of scientific software developer/engineer experiences
• Educational Background: Ph.D. or M.S. in Computer Science, Computational Chemistry, Chemical Engineering, Materials Science, or a related field, with a focus on molecular simulations.
• Technical Skills:
• Proficiency in molecular dynamics packages (e.g., LAMMPS, GROMACS, CP2K, NAMD).
• Advanced programming skills in Python, Fortran, and C++, with expertise in software development and test-driven practices.
• Familiarity with GPU-accelerated DFT packages like GPU4PySCF and machine learning frameworks for molecular property prediction.
• Experience with software package deployment, optimization, and maintenance in HPC and cloud platforms.
• Knowledge of data analysis and visualization tools (e.g., NumPy, Pandas, Matplotlib), and skills in parallel computing, multi-threading, and optimizing software for performance on large datasets.
• Domain Knowledge: Solid understanding of chemical interactions, thermodynamics, and statistical mechanics in molecular simulations.
• Soft Skills: Strong communication skills, the ability to collaborate across disciplines, and a proactive, solution-oriented approach.

Preferred Experience:

• Experience with molecular modeling tools such as Gaussian, VASP, or Quantum ESPRESSO.
• Proven track record in managing and scaling computational simulations on distributed systems or clusters.
• Familiarity with machine learning frameworks and the integration of AI for molecular property prediction.

Who Will Thrive in This Role:

• A skilled developer passionate about molecular simulations and machine learning, with a commitment to creating efficient, scalable, and robust software solutions.
• An effective problem solver who values documentation and reproducibility.
• A proactive mentor and collaborator who can translate complex research needs into practical computational tools.