Principal Machine Learning Engineer - Green Hydrogen

We are seeking a Machine Learning Principal Scientist to join our Electrolyzer Technology team. The ideal candidate will leverage advanced AI / ML techniques to model, predict, and optimize the performance and durability of electrolyzer stacks and materials. This role combines machine learning with electrochemistry and physics to accelerate discovery and innovation in green hydrogen technologies.

Key Responsibilities

• Develop and deploy physics-informed machine learning models that integrate electrochemical principles with AI / ML for accurate prediction of stack behavior.
• Build degradation models to predict lifetime performance, failure modes, and durability of electrolyzer stacks and components.
• Apply advanced ML techniques (graph neural networks, reinforcement learning, VAEs, GANs, diffusion models) for material discovery and process optimization.
• Approximate complex physical, chemical, and electrochemical processes through hybrid ML–physics frameworks.
• Collaborate with material scientists, electrochemists, and engineers to integrate AI-driven insights into design, testing, and scale-up of electrolyzer technology.
• Stay at the forefront of advances in AI / ML, computational chemistry, and green energy, and translate them into practical R&D applications.