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# Principal Scientist / Associate Director, Agentic AI Research for Materials Science

- **Company:** Lila Sciences, Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $288,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Mining, Systems Theories, Python (Programming Language), Machine Learning, Software Deployment, Systems Architecture, Workflow Management Systems, Large Language Models, Agentic-AI, Information Technology, Machine Learning Operations
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/principal-scientist-associate-director-agentic-ai-research-for-materials-science-san-francisco-ca--09e15981-ecfc-4d0b-a4a3-c41bf4c79fb6

## About the Role

Material Science, Artificial Intelligence (AI), Scientific Research, Material Science, Artificial Intelligence (AI), Coaching, Technical Leadership, Team Lead/Manager, System Architecture, Mentoring, * PhD in Computer Science, Machine Learning, Materials Science, Chemistry, Physics, or a related field, with 5+ years of post-PhD research and applied ML experience.

 * Track record of building and shipping agentic systems, ML pipelines, or autonomous research workflows that delivered measurable scientific or product impact.
 * Deep expertise across modern ML, NLP, and reasoning: LLMs, agentic frameworks, tool use, planning, data extraction, and multi-modal data.
 * Working knowledge of materials science, computational chemistry, or condensed-matter physics sufficient to ground agent behavior in real scientific constraints.
 * Proficiency in Python and the ML software stack, with strong engineering habits around reproducibility, testing, and production deployment.
 * Experience leading scientists and engineers: setting technical direction, hiring, mentoring, and developing team members.
 * Clear written and verbal communication; able to translate between research, engineering, and program stakeholders.

Bonus Points For

 * Publications, patents, or open-source contributions in agentic AI, scientific ML, or autonomous research systems.
 * Experience integrating agents with real-world materials science tasks and familiarity with materials data representations and ontologies.
 * Production experience with workflow orchestration and distributed compute on cloud or HPC.
 * Community recognition: invited talks, conference organizing, or community leadership in agentic AI or scientific AI.