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# ML Research Scientist I/II, Multimodal Data Extraction

- **Company:** Lila Sciences, Inc.
- **Location:** Cambridge, United States
- **Salary:** $176,000.0 - $304,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Mining, Data Structures, Graph Database, Machine Learning, Language Modeling, Open Source Technology, Pytorch, Large Language Models, Information Technology, HuggingFace
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/ml-research-scientist-i-ii-multimodal-data-extraction-lila-sciences-7844988

## About the Role

* PhD (or equivalent research experience) in Computer Science, Chemistry, Materials Science, or related field.
 * Expertise in machine learning, NLP, and vision-language modeling using PyTorch and Hugging Face Transformers.
 * Proven ability to train, fine-tune, and evaluate LLMs and multimodal models for scientific data extraction.
 * Strong understanding of data structures and representations used in the physical sciences.
 * Demonstrated research impact through publications, preprints, or open-source work (e.g., NeurIPS, ICLR, ICML, ACL, EMNLP, Scientific Journals).

Bonus Points For

 * Experience with multimodal fusion architectures and document-level understanding.
 * Knowledge of scientific document parsing (OCR, table extraction, figure-caption linking).
 * Familiarity with knowledge graph construction or reasoning systems for science.
 * Experience with noisy or heterogeneous real-world scientific data.
 * Collaborative mindset and passion for advancing AI in the physical sciences.

## Description

* Research and develop AI systems that extract and structure knowledge from diverse scientific sources.
 * Design and fine-tune large language, multi-modal and specialized models for factual, interpretable data extraction.
 * Build scalable pipelines for unstructured and heterogeneous scientific data, integrating text, tables, and visuals.
 * Collaborate with domain experts to align extracted data with real-world discovery workflows.
 * Publish research that advances the state of the art in multimodal understanding and AI-driven knowledge extraction.


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