Co-Op, Structuring Scientific Data for Discovery

Lila Sciences, Inc.; Cambridge, San Francisco (MA, CA); On-site; USD 28,000 - 41,000; Part time

Job summary

Lila Sciences, Inc. is seeking a Data Extraction Co-Op in Cambridge, MA and San Francisco, CA to help turn unstructured scientific knowledge into structured signals that power downstream Lila applications.

You will fine-tune models for data extraction, build pipelines, and contribute to production-ready code. Collaborate with researchers and engineers, document findings, and potentially contribute to publications or open-source projects.

Qualifications

• Pursuing a Bachelor's, Master's, or PhD in CS, chemistry, materials science, physics, biology, or chemical engineering.
• Solid foundation in machine learning fundamentals and Python.
• Familiarity with NLP or computer vision concepts.
• Curiosity about scientific data and willingness to learn quickly in a research setting.
• Clear written and verbal communication.

Responsibilities

• Fine-tune and evaluate language, multimodal, or specialized models for scientific data extraction.
• Build retrieval and RAG pipelines surfacing relevant documents, tables, and figures.
• Generate and validate structured datasets extracted from scientific literature and patents.
• Run end-to-end pipelines and analyze results against clear evaluation criteria.
• Document findings and present them to the team.
• Contribute to a publication or open-source project where the work supports it.

Skills

Machine Learning basics

Python

NLP

Communication

Education

Bachelor's/Master's/PhD in CS, chemistry, materials science, physics, biology, or chemical engineering

Job description

Co-Op, Structuring Scientific Data for Discovery

Cambridge, MA USA; San Francisco, CA USA

Lila Sciences builds AI systems that accelerate discovery across the physical and life sciences. Our team turns unstructured scientific knowledge, including literature, patents, and technical reports, into structured signals that power downstream Lila applications.

As a Data Extraction Co-Op, you will work alongside research scientists and engineers on a focused sub-problem in this stack. You will fine-tune and evaluate models for scientific knowledge extraction and retrieval, build pipelines for messy real-world data, and ship work that flows into production systems.

What You'll Be Building

• Fine-tune and evaluate language, multimodal, or specialized models for scientific data extraction
• Build retrieval and RAG pipelines surfacing relevant documents, tables, and figures
• Generate and validate structured datasets extracted from scientific literature and patents
• Run end-to-end pipelines and analyze results against clear evaluation criteria
• Document findings and present them to the team
• Contribute to a publication or open-source project where the work supports it

What You'll Need to Succeed

• Pursuing a Bachelor's, Master's, or PhD in CS, chemistry, materials science, physics, biology, or chemical engineering
• Solid foundation in machine learning fundamentals and Python
• Familiarity with NLP or computer vision concepts
• Curiosity about scientific data and willingness to learn quickly in a research setting
• Clear written and verbal communication

Bonus Points For

• Coursework or projects involving multimodal models or document understanding (OCR, table and figure extraction)
• Experience with LLM applications, embeddings, or retrieval systems (chunking, reranking, vector search)
• Experience building evaluation sets or annotation workflows
• Experience working with messy real-world data
• Interest in scientific document parsing

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.

Lila Sciences iscommitted to equal employment opportunityregardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

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