Machine Learning Researcher at Astera Institute focusing on data - efficient and general model induction. Collaborating on innovative architectures with a focus on performance and throughput.
About the role
- Data & Evaluation Applied AI Scientist at SES AI Corp., focusing on integrating AI into battery technology for energy transition. Collaborating with experts in a dynamic, innovative environment for impactful scientific projects.
Responsibilities
- Data Curation & Validation: Translate deep Battery Materials Knowledge and next-generation battery concepts into correctly structured, high-quality, AI-trainable data.
- Lead processes for rigorous data validation, cleaning, and annotation to ensure consistency and correctness across all datasets.
- Oversee the creation and management of benchmark datasets and design domain-specific multimodal evaluations to test model accuracy.
- AI System Quality & Correctness: Partner closely with AI architecture and engineering teams to ensure the correctness, reliability, and scientific reasoning quality of models, including LLM creation and multi-agent orchestration.
- Implement techniques, including those inspired by reinforcement learning (RLHF), to tune and validate model behavior against established scientific principles.
- Ensure that resulting models accurately understand molecular chemistry, materials data, and complex scientific reasoning in the battery domain.
- Strategy & Collaboration: Drive the application of Battery Informatics principles across all data pipelines and modeling efforts.
Requirements
- Education: Ph.D. in Chemical Engineering with a focus on Lithium battery systems, Materials Science, or a closely related computational/domain field.
- Domain Expertise: Deep expertise in battery materials, particularly knowledge required to convert complex, real-world data into AI-trainable formats.
- Data Quality & Validation: Proven experience in data validation, annotation, and benchmark creation for complex scientific or engineering datasets.
- AI Exposure: Experience working with advanced AI systems, including familiarity with LLM pipelines and the principles of multi-agent orchestration.
- Applicable Background: Experience in roles such as Applied Scientist in Molecular/Materials AI or similar specialist roles focused on AI system quality in a scientific domain.
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.
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