ML Research Scientist I/II, Multimodal Data Extraction

About this role

Your Impact at LILA

As a ML Research Scientist - Multimodal Data Extraction, you will advance Lila’s vision of scientific superintelligence by developing foundation models that autonomously read, interpret, and structure scientific knowledge across text, images, and experimental data in the physical sciences. Your research will help unify the world’s scientific information into machine-understandable form, powering reasoning, prediction, and autonomous discovery across materials science and chemistry.

What You'll Be Building

• Research and develop AI systems that extract and structure knowledge from diverse scientific sources.

• Design and fine-tune large language, multi-modal and specialized models for factual, interpretable data extraction.

• Build scalable pipelines for unstructured and heterogeneous scientific data, integrating text, tables, and visuals.

• Collaborate with domain experts to align extracted data with real-world discovery workflows.

• Publish research that advances the state of the art in multimodal understanding and AI-driven knowledge extraction.

What You’ll Need to Succeed

• PhD (or equivalent research experience) in Computer Science, Chemistry, Materials Science, or related field.

• Expertise in machine learning, NLP, and vision–language modeling using PyTorch and Hugging Face Transformers.

• Proven ability to train, fine-tune, and evaluate LLMs and multimodal models for scientific data extraction.

• Strong understanding of data structures and representations used in the physical sciences.

• Demonstrated research impact through publications, preprints, or open-source work (e.g., NeurIPS, ICLR, ICML, ACL, EMNLP, Scientific Journals).

Bonus Points For

• Experience with multimodal fusion architectures and document-level understanding.

• Knowledge of scientific document parsing (OCR, table extraction, figure-caption linking).

• Familiarity with knowledge graph construction or reasoning systems for science.

• Experience with noisy or heterogeneous real-world scientific data.

• Collaborative mindset and passion for advancing AI in the physical sciences.

Compensation

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.

Expected Base Salary Range
$176,000—$304,000 USD

About LILA

Lila Sciences is building Scientific Superintelligence™ 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 Factory™ 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.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual…