New

Co-Op, Structuring Scientific Data for Discovery

United StatesUnited States·San Francisco,Cambridgemid
Other
1 views0 saves0 applied

Quick Summary

Overview

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,

Technical Tools
Other

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.

  • 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
  • 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

Nice to Have

~1 min read
  • 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

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 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.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

Location & Eligibility

Where is the job
Cambridge, United States
On-site at the office
Who can apply
US

About this job

Who can apply
United States
Posted
Today
Employer
has 125 open jobs on Jobera in 2 countries.

Listing Details

Posted
October 28, 2026
First seen
October 28, 2026
Last seen
October 28, 2026

Posting Health

Days active
0
Repost count
0
Trust Level
67%
Scored at
October 28, 2026

Signal breakdown

freshnesssource trustcontent trustemployer trust
Newsletter

Stay ahead of the market

Get the latest job openings, salary trends, and hiring insights delivered to your inbox every week.

A
B
C
D
Join 12,000+ marketers

No spam. Unsubscribe at any time.

Co-Op, Structuring Scientific Data for Discovery