Data Extraction Co-op

Lila Sciences; Cambridge (MA); On-site; USD 30,000 - 39,000; Part time

Job summary

Lila Sciences is building AI systems to accelerate discovery across physical and life sciences. As a Data Extraction Co-Op, you will collaborate with researchers to fine-tune models, build data pipelines, and ship components that feed production systems.

You will develop expertise in scientific data extraction and retrieval, work with messy real-world data, and contribute to publications or open-source efforts while learning quickly in a research setting.

Qualifications

• Solid foundation in machine learning and Python.
• Familiarity with NLP or computer vision concepts.
• Curiosity about scientific data and ability to learn quickly.

Responsibilities

• Fine-tune and evaluate models for scientific data extraction.
• Build retrieval and RAG pipelines for documents, tables, figures.
• Generate structured datasets from literature and patents.
• Run end-to-end pipelines and analyze results against criteria.
• Document findings and present to the team.
• Contribute to publications or open-source projects.

Skills

Python

ML fundamentals

NLP/CV concepts

Scientific data curiosity

Strong communication

Education

CS/chemistry/materials sci/physics/biology/ChemE

Tools

NumPy/Pandas

Git

OCR

Job description

Your Impact at LILA

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.

We’re All In

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

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