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1 week ago
We are seeking a skilled Research Architect to drive the development and implementation of cutting-edge LLM architectures, prompt engineering strategies, and LLM training techniques tailored to healthcare and oncology text. As a key member of our team, you will be responsible for driving proof-of-concepts from rapid iterations to rigorous experimental evaluations on clinical-text tasks.
Key Responsibilities:
- Develop novel LLM architectures, adapter modules, and prompt-tuning strategies for tasks such as clinical note summarization, entity extraction, and question answering.
- Define evaluation protocols, run ablation studies, and analyze results to quantify improvements in accuracy, robustness, and domain generalization.
- Build end-to-end POCs demonstrating how research breakthroughs translate into tangible gains on real healthcare datasets.
- Work alongside NLP engineers and MLOps teams to hand off production-ready prototypes; present findings in regular research seminars and contribute to internal or external publications.
To succeed in this role, you must have a solid background in Computer Science, Computational Linguistics, AI/ML, or a related field, with 2-3 years of professional R&D experience in NLP or ML research roles. You should possess strong Python skills and deep familiarity with PyTorch or TensorFlow, as well as proficiency in working with NLP frameworks, deep learning libraries, and common data preprocessing techniques. Additionally, expertise in prompt engineering, few-shot learning, and fine-tuning for domain-specific tasks is highly desirable.
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