Hybrid Scientist, Molecular AI Architecture

at SES AI Corp

• Job title: Scientist, Molecular AI Architecture
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Location requirements: Hybrid, Woburn, United States

About the role

• Scientist developing innovative AI systems for battery technology at SES AI. Contributing to energy transition through material discovery and AI integration.

Responsibilities

• Architect novel AI systems and deep neural architectures (e.g., Transformers, CNNs) inspired by principles of systems neuroscience and neural coding principles.
• Design and implement large-scale multimodal foundation models and agentic AI systems capable of complex reasoning over molecular and battery datasets.
• Develop methods for model interpretability, representation engineering, and causal reasoning to ensure AI results are explainable and trustworthy for materials science.
• Lead software development efforts for high-performance computing (HPC), focusing heavily on GPU programming and scaling the training and inference efficiency of large neural networks.
• Optimize complex ML frameworks (like JAX) within systems and cluster computing environments (e.g., Singularity).
• Create automated data-labeling and behavioral encoding models specifically designed to enhance Molecular AI training and data efficiency.
• Apply Scientific ML principles to complex molecular and battery datasets, translating biological computation concepts into practical AI solutions for materials discovery.

Requirements

• Education: Ph.D. in Computational and Systems Biology, Computational Neuroscience, or a closely related quantitative field.
• Core Expertise: Deep, demonstrated expertise in systems neuroscience, machine learning, and the design and implementation of deep neural architecture.
• HPC Software: Proven experience with software development for High-Performance Computing (HPC) environments, including expert-level GPU programming.
• Model Design: Practical experience in designing and training foundation models and working with concepts like multi-agent reasoning models.
• Interpretability Focus: Demonstrated work in model interpretability and representation engineering applied to complex scientific data.

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.