Research Scientist, Photonic Materials Discovery

• PhD or equivalent experience in Physics, Materials Science, Chemistry, Electrical Engineering, or a related field.
• Strong background in computational condensed-matter physics, materials science, physical chemistry, or a related discipline, with experience studying functional optical, dielectric, or electronic materials.
• Expertise in electronic-structure methods and calculating and interpreting dielectric, optical, vibrational, polarization, or related response properties using perturbative, finite-field, Berry-phase, or comparable methods.
• Working knowledge of crystallographic symmetry, electronic structure, lattice dynamics, light–matter interaction, and structure–property relationships.
• Experience with established electronic-structure packages and reproducible HPC or cloud workflows, including scheduling, data management, and automated analysis; strong Python and scientific software skills.
• Familiarity with agentic AI, tool-calling, or workflow orchestration and the design of reliable, auditable workflows across scientific tools.

• Experience with materials or device concepts relevant to electro-optics and integrated photonics, including ferroelectrics, semiconductors, oxides, nitrides, chalcogenides, or low-dimensional materials.
• Familiarity with advanced electronic-structure, excited-state, finite-temperature, or multiscale methods—such as hybrid-functional, many-body, molecular-dynamics, or effective-Hamiltonian approaches—when standard DFT is insufficient.
• Experience modeling defects, surfaces, interfaces, thin films, strain, or other non-ideal effects, and connecting atomistic predictions to electromagnetic, device, or process models.
• Experience building high-throughput workflows, materials data systems, surrogate models, or active-learning loops, including applications of AI/ML to computational materials science or physics-based simulation.
• Hands-on experience with agentic or tool-using systems and orchestration patterns for long-running scientific tasks, including branching, retries, checkpointing, and asynchronous execution.
• Experience designing evaluation, observability, error recovery, provenance, and human oversight for agent-driven workflows.
• Ability to communicate physical insight, uncertainty, and model limitations to cross-functional collaborators.

We offer competitive base compensation with bonus potential and generous early-stage equity.

Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including 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; and a company subsidized lunch program.

International Benefits.

Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region.

USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Lila Sciences is building Scientific SuperintelligenceTM to solve humankind's greatest challenges.

We believe science is the most inspiring frontier for AI.

Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science FactoryTM instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy.

Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance.

If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

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