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

Lila Sciences • San Francisco, MA

33d • Onsite

About The Position

Lila Sciences is seeking a Principal Scientist / Associate Director, Agentic AI Research for Materials Science. This role involves owning the technical direction for agentic AI systems applied to materials science, setting and executing a roadmap for autonomous agents that plan, run, and interpret materials experiments. The work aims to shift materials research from human-paced iteration to machine-paced experimentation through scientific reasoning and understanding. This is a player-coach role on the PS AI team, leading a small group of scientists and engineers, setting standards for scientific rigor and engineering quality, and partnering with diverse teams to implement agentic systems. The role requires owning trade-offs between research ambition and production reliability, and representing the agentic-AI direction to technical leadership. The work spans foundational research and applied delivery, with opportunities to publish, ship systems, and shape Lila's agentic capabilities.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• Define and execute the agentic AI roadmap for materials science, including agentic frameworks and retrieval-augmented generation for understanding multi-modal research data from research literature and other data sources.
• Lead the design of agentic frameworks grounded in fundamental scientific understanding and the state of the art, and deliver end-to-end systems on real-world projects.
• Hire, mentor, and grow a small cross-functional team of scientists and engineers; set the bar for scientific rigor, code quality, and reproducibility.
• Partner with diverse teams at Lila to push the state of the art and deliver systems that integrate with experimental infrastructure and land on real programs.
• Track state-of-the-art in agentic AI, scientific ML, data extraction, and reasoning models; translate external advances into internal direction, and publish or present where the science merits it.

Benefits

• Competitive base compensation with bonus potential and generous early-stage equity.
• Medical, dental, and vision coverage.
• Employer-paid life and disability insurance.
• Flexible time off with generous company wide holidays.
• Paid parental leave.
• An educational assistance program.
• Commuter benefits, including bike share memberships for office based employees.
• A company subsidized lunch program.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree