Battery Materials Electrochemistry Expert

About Us:

SES AI Corp. (NYSE: SES) is dedicated to accelerating the world’s energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting‑edge machine learning into our research and development. Our AI‑enhanced, high‑energy‑density and high‑power‑density Li‑Metal and Li‑ion batteries are unique; they are the first in the world to utilize electrolyte materials discovered by AI.

This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage, robotics, and drones.

• 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.

The SES AI Hermes team is seeking an exceptional Battery Materials Electrochemistry Expert to serve as the cornerstone for our experimental validation and R&D pipeline. This role is centered on advanced battery chemistry and SEI engineering, requiring deep practical expertise to translate R&D outputs into high‑quality, AI‑trainable data for accelerated materials discovery. As a Senior Materials Scientist, you will drive the design and execution of experimental programs that fuel our materials informatics models.

• Battery R&D & Experimentation
  • Lead the design and execution of experiments (DOE design) focused on advanced Lithium battery systems, including solid‑state and Li‑ion chemistry.
  • Drive electrolyte R&D, focusing on additive optimization and meticulous SEI (Solid Electrolyte Interphase) engineering to enhance battery performance and safety.
  • Oversee the complete battery development lifecycle, including raw‑material chemistry, electrode fabrication, electrochemical testing, and prototype validation.
• Characterization & Validation
  • Perform advanced electrochemical testing and characterization (e.g., impedance, cycling) to define safety and performance metrics.
  • Generate clean, structured data from experiments that meets the rigorous requirements for training AI/ML models.
  • Bridge the gap between computational modeling and experimental validation, serving as a hybrid expert for material design iteration.
• Category (e.g., Model Optimization & Implementation)
  • Collaborate with the AI/ML team to understand model requirements, contributing domain expertise to molecular property prediction, material screening, and generative chemistry applications.

• Education:
  
  Ph.D. in Materials Science, Chemical Engineering, Applied Physics, or a closely related field. A background in Mechanical & Aerospace Engineering with a strong materials focus is also acceptable.
• Core Battery Expertise:
  Deep, hands‑on expertise in Lithium battery chemistry, including fundamental understanding of Li‑ion and solid‑state systems.
• Experimental
  
  Skills:
  
  Proficiency in advanced electrochemical testing and materials characterization techniques.
• Interfacial Engineering:
  Proven experience in electrolyte formulation, additive optimization, and SEI engineering.
• R&D Process:
  Experience managing the full battery development lifecycle, from raw material to prototype validation.

• Hybrid Expertise:
  Demonstrated experience working in a hybrid computational modeling + experimental validation capacity.
• AI/ML Exposure:
  Direct experience or strong understanding of the application of AI/ML models to materials informatics, molecular property prediction, and multi‑physics simulations.