Co-Op, Structuring Scientific Data for Discovery
- Location
- Cambridge, MA USA; San Francisco, CA USA
- Listed
- 12 days ago
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
We're All In
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
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.
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.
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.
Equal opportunity and legal notices
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.
From Lila Sciences's careers page, first listed on Rolev.ai on October 28, 2026. Rolev.ai is not the employer.
How Rolev.ai helps with this application
Rolev.ai is a job search and application tool for US job seekers. For this Co-Op, Structuring Scientific Data for Discovery role at Lila Sciences, it shows how your resume fits, tailors your resume to the posting, and prepares the application for you to review.
See how you fit
Openings from employer career sites are ranked against your whole resume—and searchable inside Claude, ChatGPT, and Cursor via Rolev.ai MCP.
Tailor without inventing
Every change to your resume is checked against your original. New experience goes in only with your yes—zero fabricated claims.
Draft the full kit
Tailored and Full Match resumes, role-specific cover letters, and answers to employer screening questions are prepared in seconds.
1-Click Extension Autofill
The Chrome extension fills the employer's Greenhouse, Workday, Lever, or Ashby form in 1 click. You review it and press Submit.
Common questions
Where is the Co-Op, Structuring Scientific Data for Discovery job at Lila Sciences located?
This Co-Op, Structuring Scientific Data for Discovery position at Lila Sciences is located in Cambridge, MA USA; San Francisco, CA USA. Always check Lila Sciences's application page for specific state eligibility or relocation policies.
How do I apply for the Co-Op, Structuring Scientific Data for Discovery position at Lila Sciences?
This listing links directly to Lila Sciences's Greenhouse application page. You can apply directly on Lila Sciences's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Greenhouse application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.