Battery Electrolyte Scientist & Materials Chemistry Leader Greater Boston (Woburn, MA) – On-sit[...]

Solid Energy Systems; Woburn (MA); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive health coverage

Equity/stock options

Professional growth opportunities

Job summary

A leading energy transition company is seeking a Battery Electrolyte Scientist & Materials Chemistry Leader. This role involves directing R&D programs for next-generation battery systems, integrating AI in research, and managing multidisciplinary teams. Required qualifications include a Ph.D. in relevant fields, proven leadership experience, and expertise in materials chemistry. The position offers competitive salary, benefits, and opportunities for professional growth in an innovative environment.

Qualifications

• Ph.D. in Materials Science or related field required.
• Proven leadership in R&D and multidisciplinary team management.
• Deep expertise in materials chemistry and interfacial science.

Responsibilities

• Direct complex electrolyte R&D programs focused on next-generation battery systems.
• Lead multi-R&D teams composed of chemists, data scientists, and engineers.
• Oversee SEI engineering and additive optimization programs.

Skills

Electrochemical research

AI integration

Data-driven experimentation

Interfacial science

Additive optimization

Education

Ph.D. in Materials Science

Ph.D. in Chemical Engineering

Ph.D. in Electrochemistry

Tools

Molecular informatic tools

Job description

Battery Electrolyte Scientist & Materials Chemistry Leader

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.

What we Need:

The SES AI Hermes team is seeking an exceptional Battery Electrolyte Scientist & Materials Chemistry Leader to serve as an R&D leader specializing in electrolyte development and interfacial chemistry. This role is critical for producing experimentally validated battery component data, guiding AI model training, and defining the materials innovation roadmap for next‑generation energy storage systems. As an Electrolyte Scientist and R&D Leader, you will direct key experimental programs and manage the strategic interface between chemistry and AI.

Essential Duties and Responsibilities:

• Direct complex electrolyte R&D programs focused on next‑generation battery systems, ensuring alignment with customer and product requirements (e.g., safety, cyclability, low/high temperature performance).


• Lead multi‑R&D teams composed of chemists, data scientists, and engineers to achieve key innovation milestones.


• Define the materials innovation roadmap, particularly related to electrolyte formulation and interfacial science.
  


• Oversee SEI (Solid Electrolyte Interphase) engineering and additive optimization programs, leveraging expertise in fundamental materials chemistry.


• Lead cell‑level validation and the integration of new electrolytes into prototype cells.


• Produce high‑quality, experimentally validated battery component data, guiding AI model training by ensuring data quality, experimental reproducibility, and comprehensive parameter space coverage (Data‑driven experimentation).
  


• AI Integration & Tools


• Utilize molecular informatic tools to accelerate battery component optimization cycles, effectively bridging experimental data with AI‑generated candidates.
  

Education and/or Experience:

• Education: Ph.D. in Materials Science and Engineering, Chemical Engineering, Electrochemistry, or a closely related materials chemistry field.


• R&D Leadership: Proven background as an electrochemical researcher and R&D leader experienced in directing technical programs and managing multi‑disciplinary research teams.


• Core Chemistry Expertise: Deep expertise in fundamental materials chemistry, interfacial science, additive optimization, and Solid‑Electrolyte Interphase (SEI) engineering.


• Validation Experience: Extensive experience in cell‑level validation and advanced characterization techniques, demonstrating an ability to integrate new materials into prototype cells.


• Data Focus: Demonstrated experience in data‑driven experimentation and structuring chemistry data for AI model consumption.
  

Preferred Qualifications:

• Industry Focus: Previous experience at leading battery manufacturers, electrolyte R&D teams, or applied materials chemistry labs, especially those focused on next‑generation battery and energy storage systems.


• Program Alignment: Strong track record of successfully aligning R&D execution with clear customer and product requirements.


• Informatics Tooling: Ability to use or integrate results from molecular informatic tools for component optimization.