Senior Applied Scientist

Senior Applied Scientist

Oracle Health Data Intelligence (HDI) is building AI-powered solutions that help healthcare organizations improve population health. We are seeking a Senior Applied Scientist to develop AI capabilities, with an emphasis on large language models, agentic systems, model post-training, and evaluation. This is a hands-on individual contributor role for a scientist with strong programming skills and a practical approach to experimentation. You will develop models, build agents, and implement training and evaluation workflows, working with scientists and engineers to deliver reliable, production-ready systems.

Responsibilities

What You'll Do

• Develop AI/ML components from data preparation and experimentation through deployment and monitoring.
• Build and improve LLM-based agents incorporating retrieval, tool use, reasoning, and orchestration.
• Apply model post-training techniques, including supervised fine-tuning and preference optimization, with guidance from experienced scientists.
• Prepare and validate datasets for training, evaluation, and continuous improvement.
• Implement and extend agent and evaluation harnesses for reproducible experimentation, trace analysis, benchmarking, and regression testing.
• Measure model and agent quality, reliability, safety, latency, and cost using established evaluation methods.
• Conduct error analysis and controlled experiments to identify failure modes and validate improvements.
• Write maintainable, production-quality Python code with appropriate testing and documentation.
• Work with engineers to integrate models and agents into production systems.
• Collaborate with product, clinical, and data partners to understand requirements and interpret results.
• Participate in technical discussions, design reviews, and code reviews.
• Explore relevant research and assess its usefulness through practical experiments.

Basic Qualifications

• Master's or PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience.
• 3+ years of relevant experience applying machine learning, data science, or AI to real-world problems, including relevant doctoral research.
• Strong Python programming skills, including experience writing tested, maintainable software.
• Hands-on experience developing LLM-based applications involving retrieval, structured outputs, tool use, or agents.
• Experience training or fine-tuning machine learning models and evaluating their performance.
• Experience creating evaluation datasets, implementing metrics, and conducting reproducible experiments.
• Solid understanding of machine learning, optimization, statistical inference, and experimental design.
• Experience with modern ML frameworks such as PyTorch, TensorFlow, JAX, or equivalent tools.
• Ability to independently complete well-defined technical work and collaborate on broader initiatives.
• Strong written and verbal communication skills.

Preferred Qualifications

• Experience with LLM post-training, including supervised fine-tuning, preference optimization, or reinforcement learning.
• Experience implementing or extending agent harnesses, tool integrations, tracing, and automated evaluations.
• Experience with synthetic data generation and human or AI feedback.
• Experience deploying models or agents and monitoring their performance.
• Familiarity with distributed training, inference optimization, or cloud-based ML platforms.
• Experience working with privacy-sensitive data or regulated environments.
• Experience with healthcare data or population health.

Level: IC3