Principal Applied Scientist

Oracle•United States,

4h•$126,200 - $264,100

About The Position

Oracle Health Data Intelligence (HDI) is building AI-powered solutions to help healthcare organizations improve population health. The Principal Applied Scientist will develop advanced AI capabilities, with an emphasis on large language models, agentic systems, model post-training, and evaluation. This is a hands-on individual contributor role that combines scientific rigor and software engineering to translate complex problems into reliable, production-ready systems. The role develops AI/ML solutions across their lifecycle, designs and builds LLM-based agents, applies model post-training techniques, and creates datasets, feedback pipelines, and evaluation infrastructure. It assesses model and agent quality, reliability, safety, latency, and cost, and works with engineering and cross-functional partners to operationalize AI systems. The position also evaluates emerging research and contributes to technical, design, and code reviews.

Requirements

PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience; alternatively, a Master’s degree with 6+ years of relevant industry experience.
10+ years of experience applying machine learning, data science, or AI to real-world problems.
Strong Python programming skills, including experience writing efficient, production-quality code with appropriate testing and documentation.
Experience building and deploying LLM-based systems, including agents, retrieval, and tool use.
Hands-on experience with model post-training, such as supervised fine-tuning, preference optimization, or reinforcement learning.
Experience developing evaluation frameworks, benchmarks, and experimental infrastructure for models and agents.
Deep understanding of machine learning, optimization, statistical inference, and experimental design.
Experience with modern ML frameworks such as PyTorch, TensorFlow, JAX, or equivalent tools.
Demonstrated ability to independently execute complex technical work and collaborate across disciplines.
Strong written and verbal communication skills.

Nice To Haves

Experience building agent harnesses and infrastructure for reliable execution, observability, and evaluation.
Experience with reward modeling, synthetic data generation, and human or AI feedback.
Experience with distributed training, inference optimization, and cloud-scale ML platforms.
Experience developing AI systems for high-reliability, privacy-sensitive, or regulated environments.
Experience with healthcare data or population health.

Responsibilities

Develop AI/ML solutions across the full lifecycle, from problem formulation and experimentation through deployment and monitoring.
Design and build LLM-based agents, including reasoning, planning, retrieval, tool use, and orchestration.
Apply model post-training techniques, including supervised fine-tuning, preference optimization, and reinforcement learning where appropriate.
Build high-quality datasets and feedback pipelines for training, evaluation, and continuous improvement.
Implement agent and evaluation harnesses supporting reproducible experimentation, trace analysis, benchmarking, and regression testing.
Evaluate model and agent quality, reliability, safety, latency, and cost using automated methods and expert feedback.
Conduct rigorous error analysis and controlled experiments to identify failure modes and improve performance.
Write scalable, maintainable production code in Python and work with engineers to operationalize AI systems.
Collaborate with product, clinical, data engineering, security, and compliance partners to understand requirements and assess results.
Contribute to technical discussions, design reviews, and code reviews.
Evaluate emerging research and apply methods that deliver measurable improvements.

Benefits

Medical, dental, and vision insurance, including expert medical opinion.
Short-term and long-term disability insurance.
Life insurance and accidental death and dismemberment (AD&D) insurance.
Supplemental life insurance for employees, spouses, and children.
Health care and dependent care Flexible Spending Accounts.
Pre-tax commuter and parking benefits.
401(k) Savings and Investment Plan with company match.
Flexible or accrued paid vacation, depending on employee eligibility and position.
11 paid holidays.
72 hours of paid sick leave upon hire, refreshing each calendar year, with unused balance carrying over up to a maximum cap of 112 hours.
Paid parental leave.
Adoption assistance.
Employee Stock Purchase Plan.
Financial planning and group legal benefits.
Voluntary benefits including auto, homeowner, and pet insurance.
Bonus, equity, and compensation deferral may be available.
Volunteer programs.