Senior Applied Scientist, Sirona Medical

• PhD in Data Science, Computer Science, Machine Learning, Computational Linguistics, or related fields; or Master's degree combined with equivalent relevant industry experience
• Strong expertise in traditional machine learning techniques (supervised/unsupervised), statistics, and hypothesis testing
• 8+ years of experience applying machine learning and AI to real-world problems, with a focus on NLP and LLMs
• Proficiency with Python, SQL, and popular data science libraries such as pandas, NumPy, scikit-learn, and PyTorch
• Proven experience with generative AI and NLP methods, including prompt engineering, embeddings/vector databases, retrieval-augmented generation (RAG), LLM evaluation, and fine-tuning techniques
• Strong track record in deploying AI models to production and conducting rigorous model performance evaluations. Hands-on experience fine-tuning closed and open-source models and integrating them into production systems
• Strong understanding of model deployment pipelines and experience maintaining AI models in a production environment
• Ability to communicate effectively with both technical and clinical teams, translating complex AI concepts into actionable insights and performant models

Desirable

• We are seeking a Senior Applied Scientist, Generative AI (GenAI) to lead the development and deployment of advanced AI models that power critical clinical applications
• This role will balance hands-on model development with close collaboration with engineering teams to ensure seamless integration and optimization of AI models in production environments
• You'll play a pivotal role in driving innovation across multiple AI initiatives, from clinical report generation to agentic workflows that utilize natural language commands
• Design, develop, and fine-tune generative AI models for clinical applications, including semi-automated medical report generation, patient data summarization, and clinical decision support
• Implement robust evaluation pipelines to benchmark model performance, detect drift, and ensure continuous improvement
• Prototype and integrate AI models into real-world healthcare applications, collaborating with product and engineering teams to push models into production
• Conduct research and experimentation to optimize LLMs, NLP models, and multimodal approaches for healthcare tasks
• Explore and prototype agentic workflows that leverage natural language voice commands to enhance clinical workflows
• Evaluate and integrate third-party algorithms and AI models, leveraging LLMs to improve functionality and system performance
• Stay on top of emerging trends and advancements in AI, with a focus on identifying opportunities for innovation in clinical applications