AI Scientist I/II, Representation Learning for Materials Science

AI Scientist I/II, Representation Learning for Materials Science Join our Physical Science division to create, deploy and transform state‑of‑the‑art approaches for representation learning for diverse data structures related to materials science. Partner with materials science experts and other teams to develop novel representations and algorithms that capture fundamental structure and relationships across multimodal data streams, enabling frontier materials discovery. What You’ll Be Building Physics‑Informed, Multi‑Modal Representation Learning Algorithms: Design and implement novel representation learning architectures for materials data spanning diverse applications and underlying data types. Self‑Supervised & Unsupervised Learning Methods: Develop self‑supervised and unsupervised learning approaches to discover meaningful materials representations and learned embeddings originating from diverse data streams. Real‑World Validation & Deployment: Partner with materials scientists, chemists, and software engineers to deploy algorithms and models for real‑world materials design cases accelerating discovery. Cross‑Functional Partnership: Work closely with R&D leadership, product managers, and automation specialists to translate scientific questions into modeling strategies, learning methods, and deployment for materials discovery. What You’ll Need To Succeed Proficiency in Python, deep learning frameworks, and end‑to‑end workflow deployment for scalable learning algorithms. Understanding of state‑of‑the‑art representation learning methods (self‑supervised, unsupervised) and physics‑informed inductive biases (geometric deep learning methods), and their application to scientific problems such as materials science, chemistry, or biology. Elementary understanding of materials science, physics and chemistry and how relevant principles can be infused into architectures and learning algorithms. Strong self‑starter and independent thinker with strong attention to detail. Demonstrated industry experience or academic achievement. Excellent communication and presentation skills, capable of conveying technical information clearly and thoroughly. Eager to work with highly skilled and dynamic teams in a fast‑paced, entrepreneurial, and technical setting. Bonus Points For PhD in Materials Science, Computer Science, Physics, Chemistry, or related field with strong publication record in machine learning (NeurIPS, ICML, ICLR) and scientific venues (Nature, Science, Cell Press Matter, IOP). Experience with computational materials science methods (DFT, Molecular Dynamics). Understanding of experimental materials science techniques related to synthesis and characterization. Experience creating representation learning algorithms for uncommon data structures. About Lila Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We introduce scientific superintelligence to solve humankind’s greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at Compensation We expect the base salary for this role to fall between $176,000—$304,000 USD per year, along with bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact. We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto. Seniority level Entry level Employment type Full‑time Job function Engineering and Information Technology Industries Technology, Information and Internet Referrals increase your chances of interviewing at Lila Sciences by 2x. #J-18808-Ljbffr Lila Sciences