About the role#
As a Data Extraction Co-Op, you will join our Physical Sciences AI team to help turn unstructured scientific knowledge into structured data. You will work with research scientists and engineers to solve specific problems within our data stack, focusing on literature, patents, and technical reports. This role involves hands-on experience with model fine-tuning and pipeline development for real-world scientific data.
What you'll do#
- Contribute to AI systems that extract and structure knowledge from scientific literature and patents.
- Fine-tune and evaluate language, multimodal, or specialized models for data extraction.
- Build and test pipelines that structure unstructured scientific data across text, tables, and visuals.
- Run extraction pipelines, analyze results, and document your findings.
- Share your work through team presentations, write-ups, or contributions to publications or open-source projects.
What you'll need#
- Currently pursuing a Bachelor's, Master's, or PhD in Computer Science, Chemistry, Materials Science, or a related field.
- A solid foundation in machine learning fundamentals and Python.
- Familiarity with NLP or computer vision concepts.
- Curiosity about scientific data and a willingness to learn quickly in a research setting.
- Experience with coursework or projects involving multimodal models or document understanding, such as OCR or table and figure extraction.
Location & details#
- Location: Cambridge, Massachusetts, USA.
- Work Modality: On-site.
- Term: Rolling.
- This is a full-time, paid position.
About Lila Sciences
Lila Sciences operates as a scientific superintelligence platform and autonomous lab. The company focuses on life, chemistry, and materials science. It applies artificial intelligence to the scientific method to assist with research in human health and sustainability. Founded in 2023, the organization maintains its headquarters in Cambridge, Massachusetts. It currently employs 474 people.
How to get in at Lila Sciences
Applying early gives you a distinct advantage at Lila Sciences, as recruiters often review candidates before the applicant pool grows too large. Intern Insider sends an instant alert the moment a role matching your target is published, helping you stay at the front of the line. This timing matters when competition for technical roles is high. You can use this lead to prepare your materials before the position gains wider visibility. Reaching out to the right people often yields better results than submitting an application into a general queue. Intern Insider surfaces the recruiters behind the company's roles, which allows you to contact them directly for a referral or to ask specific questions about the work. A direct connection can improve your response rates and help you stand out from the pile.
