Senior Applied Scientist

Oracle; United States; On-site; USD 113,000 - 235,000; Full time

Benefits offered by this job

Bonus potential

Equity

Compensation deferral

Job summary

Oracle Health Data Intelligence (HDI) is seeking a Senior Applied Scientist to advance AI capabilities, with emphasis on large language models, agentic systems, and post‑training techniques. This is a hands‑on IC3 role for a scientist with strong programming skills and a practical approach to experimentation.

You will develop models, build agents, and design training and evaluation workflows, collaborating with scientists and engineers to deliver reliable, production‑ready systems and measurable

Qualifications

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Responsibilities

• Develop AI/ML components from data preparation 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.
• Prepare and validate datasets for training, evaluation, and continuous improvement.
• Implement and extend agent and evaluation harnesses for reproducible experimentation and benchmarking.
• 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 testing and documentation.
• Collaborate with product, clinical, and data partners to understand requirements and interpret results.

Skills

Python programming

LLM applications

Agent development

Experimentation

Model evaluation

Data processing

Production‑quality software

Retrieval augmented generation

Education

Master’s or PhD in Computer Science / ML / Statistics or related field

Tools

PyTorch

TensorFlow

JAX

Job description

Job Description

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

Qualifications

Disclaimer:
Certain U.S. based or U.S. customer or client‑facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements.

Range and benefit information provided in this posting are specific to the stated locations only

US: Hiring Range in USD from: $113,000 - $234,600 per year. May be eligible for bonus, equity, and compensation deferral.
Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business.
Candidates are typically placed into the range