Job Description
The role involves designing and implementing advanced AI architectures for materials discovery, focusing on large-scale multimodal models, high-performance computing, and explainability to accelerate the development of innovative battery technologies.
Key Responsibilities
- Design and implement novel AI systems and deep neural architectures inspired by neuroscience principles.
- Develop large-scale multimodal foundation models and agentic AI systems for complex reasoning over molecular and battery datasets.
- Create methods for model interpretability, representation engineering, and causal reasoning to ensure explainability and trustworthiness of AI results.
- Lead software development for high-performance computing environments, focusing on GPU programming and scaling neural network training and inference.
- Optimize machine learning frameworks like JAX within HPC systems and cluster environments.
- Create automated data-labeling and behavioral encoding models to enhance molecular AI training and data efficiency.
- Apply scientific ML principles to complex molecular and battery datasets, translating biological computation concepts into AI solutions for materials discovery.
Requirements
- Ph.D. in Computational and Systems Biology, Computational Neuroscience, or a closely related quantitative field.
- Deep, demonstrated expertise in systems neuroscience, machine learning, and the design and implementation of deep neural architecture.
- Proven experience with software development for High-Performance Computing (HPC) environments, including expert-level GPU programming.
- Practical experience in designing and training foundation models and working with concepts like multi-agent reasoning models.
- Demonstrated work in model interpretability and representation engineering applied to complex scientific data.
- Experience creating automated data-labeling and behavioral encoding models specifically designed to enhance Molecular AI training and data efficiency.
- Ability to architect novel AI systems and deep neural architectures such as Transformers and CNNs inspired by principles of systems neuroscience and neural coding principles.
- Experience designing and implementing large-scale multimodal foundation models and agentic AI systems capable of complex reasoning over molecular and battery datasets.
- Experience developing methods for model interpretability, representation engineering, and causal reasoning to ensure AI results are explainable and trustworthy for materials science.
- Experience leading software development efforts focusing on GPU programming and scaling the training and inference efficiency of large neural networks.
- Ability to optimize complex ML frameworks like JAX within systems and cluster computing environments such as Singularity.
Benefits & Perks
A highly competitive salary
Robust benefits package including comprehensive health coverage
Attractive equity stock options program
Opportunity to contribute to meaningful scientific projects with broad public impact
Work in a dynamic, collaborative, and innovative environment
Significant opportunities for professional growth and career development
Access to state-of-the-art facilities and proprietary technologies
Ready to Apply?
Join SES and make an impact in renewable energy
Stay Updated on Sustainability Jobs
Get the latest renewable energy jobs and career tips delivered to your inbox.
Job Alerts
Get notified about new sustainability jobs
More at SES
More jobs at SES
Senior Scientist, Electrolyte
SES
Woburn
Full Time
Feb 24
Business Development Representative BDR
SES
Woburn
ON-SITE
Jan 29
Materials Business Unit Head
SES
Woburn
Full Time
Jan 21
More jobs in Woburn, Massachusetts
Senior Staff Accountant
Unison
Woburn
Full Time
Jan 28
Accounts Payable Coordinator - Temporary to Permanent
Unison
Woburn
TEMPORARY_TO_PERMANENT
Dec 16
Accounts Payable Coordinator - Temporary to Permanent
Unison
Woburn
TEMPORARY
Jan 1