Co-Op, Data Extraction

About the role#

As a Data Extraction Co-Op at Lila Sciences, you will work alongside research scientists and engineers to turn unstructured scientific knowledge—such as literature, patents, and technical reports—into structured data. You will focus on a specific sub-problem within the extraction stack, gaining hands-on experience by fine-tuning models and building pipelines that feed into production systems.

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 with mentor guidance.
• Build and test pipelines to structure unstructured scientific data found in text, tables, and visuals.
• Run extraction pipelines, analyze results, and document your findings clearly.
• Share your work through team presentations, written reports, 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 natural language processing (NLP) or computer vision concepts.
• Curiosity about scientific data and a willingness to learn in a research environment.
• Preferred: Coursework or projects involving multimodal models or document understanding, such as OCR or table/figure extraction.

Location & details#

• Location: Cambridge, Massachusetts.
• Modality: On-site.
• Employment: Full-time, paid position.
• Term: Rolling.