Hybrid Battery Algorithm Engineer

at SES AI Corp

• Job title: Battery Algorithm Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: Python, Tensorflow
• Location requirements: Hybrid, Woburn, United States

About the role

• Battery Algorithm Engineer responsible for modeling and algorithm development for AI-enhanced batteries. Collaborating in a team to drive innovations for energy transition and battery technology at SES.

Responsibilities

• Modeling & Algorithm Development
• Design and develop core physics-based battery models and multi-physics simulations that accurately represent cell behavior.
• Engineer and apply ML/Deep Learning algorithms (using libraries like TensorFlow) for predictive modeling, safety assessment, and performance optimization.
• Develop AI4Science algorithms that merge materials physics and computational science to solve complex battery challenges.
• Digital Twin Architecture
• Architect and build the digital twin battery system—a virtual battery trained on real-time cell data to continuously monitor and predict safety and performance metrics.
• Integrate algorithms into big-data systems and infrastructure, ensuring the predictive models are scalable and robust.
• Domain Bridging & Optimization
• Maintain a hybrid understanding of data science, materials physics, algorithm infrastructure, and AI models to ensure model validity and utility.
• Utilize computational tools like COMSOL Multiphysics and finite element analysis (FEA) for complex modeling and simulation tasks.

Requirements

• Education: Ph.D. in Materials Engineering or a closely related computational/engineering field.
• Core Modeling Expertise: Deep foundational knowledge and practical experience with physics-based battery modeling and computational battery modeling.
• Algorithm Development: Expertise in applying ML/Deep Learning algorithms for predictive modeling and optimization, specifically using libraries such as TensorFlow and other neural network architectures.
• Technical Stack: Proficiency in core programming languages (Python, MATLAB) and simulation tools (e.g., COMSOL Multiphysics, finite element analysis).
• Systems Understanding: Experience with algorithm infrastructure and architecting digital twin systems.

Benefits

• 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.