Senior Applied Scientist, Generative AI (GenAI)

About Sirona Medical

At Sirona Medical, we’re building software that enables physicians to work as fast as they can think.

Each year in the U.S., billions of patient images are captured—and nearly all of them are reviewed and diagnosed by radiologists. These specialists are the central hub of diagnostic medicine: over 80% of all healthcare data flows through radiology IT systems. Yet despite their pivotal role, radiologists are overburdened by outdated, fragmented software which limits their efficiency and ultimately the quality and efficiency of care that health systems can provide patients. That’s where Sirona comes in.

We’re a San Francisco-based, cloud-native software company with employees around the world. Our deep understanding of both the practice and business of radiology has allowed us to build RadOS—a unified, AI-powered operating system powering the entire radiology workflows.

How Sirona Solves the Problem

Sirona is uniquely positioned to transform the way radiology is practiced. We're delivering the organizational shift that both individual radiologists and entire practices urgently need:

• A unified, intuitive, and platform-agnostic solution

• A streamlined workspace that makes every part of the radiologist’s workflow faster and easier

• The freedom to read from anywhere, for anyone

By cutting clicks, optimizing diagnostic time, and unlocking efficiencies that extend far beyond the reading room into all care settings, Sirona empowers radiologists—and in doing so, we help the entire healthcare system move faster, smarter, and with greater impact on patient outcomes.   For more information, please visit https://sironamedical.com/join/.

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. 

Ideally, this person would be able to work out of our San Francisco office but remote from the United States also works. If remote, we'd like this individual to be able to fly into the San Francisco office as needed to collaborate with other scientists, engineers and executives during key strategic planning sessions.  This would likely be 3-4 days in total over the course of a quarter. 

Key Responsibilities:

• 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.
  
  

Key Requirements:

• 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 rig