Experteer Overview As a Senior Scientist in the Content Authoring team within DSDH AI/ML, you shape the future of GenAI for scientific writing and knowledge management. You will work with large language models and multi-agent systems to streamline regulatory and R&D document workflows. Your work accelerates regulatory dossier authoring and supports clinical development with intelligent agents. This role offers the chance to advance safe, grounded AI solutions in a highly collaborative, multidisciplinary setting.Compensaciones / Beneficios
- Design and develop intelligent agent systems for regulatory and scientific content authoring, including writing, reviewing, editing, and refining documents based on guidelines and user input
- Advance agent memory architectures and persistent knowledge retention to enable long-horizon reasoning and chain-of-thought grounding
- Prototype and implement controls for hallucination, uncertainty quantification, and safe output generation
- Build evaluation and benchmarking frameworks for GenAI-driven content authoring, including automated evaluation suites for prompts, models, and retrieval flows
- Collaborate with regulatory writers, scientists, engineers, and IT teams to translate emerging AI methodologies into practical, production-ready solutions
- Serve as an internal domain expert for GenAI Content Authoring specific agents' systems, driving innovation and protocols across R&D
- If required, contribute to interpretation and generation of figures and plots, demonstrating multimodal AI experienceResponsabilidades
- Master's degree in AI/ML, Computer Science, Engineering, Bioinformatics, or related field with 4+ years of hands-on experience in GenAI engineering
- Hands-on experience with multi-agent frameworks such as LangGraph, DSPy, memO, or similar architectures
- Strong proficiency in Python and modern deep-learning frameworks (PyTorch, TensorFlow)
- Experience building retrieval-augmented generation (RAG) systems, including chunking, embeddings, vector databases, and reranking
- Knowledge of advanced mathematical concepts such as uncertainty quantification, probabilistic modelling, or information theory
- Experience implementing structured generation, schema enforcement, and model/tool orchestration for complex workflows
- Positive, motivated, collaborative approach with the ability to work independently and within a multidisciplinary environmentRequisitos principales
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