Oracle Healthcare Data Intelligence (HDI) is at the forefront of leveraging data and AI to transform the healthcare and life sciences industries.
Our team is dedicated to solving complex challenges in healthcare by developing innovative solutions using Generative AI, natural language processing (NLP), and large language models (LLMs).
This role is perfect for a hands-on applied scientist who’s passionate about building and optimizing models in the healthcare space.
You’ll help design and implement new AI tools that can enhance care delivery, support providers, and make health systems smarter.
Your Role
As a Senior Applied Scientist, you’ll work closely with other scientists, engineers, and product teams to build and evaluate AI models for real healthcare and biological problems.
You will collaborate with a multidisciplinary team to design, build, and deploy scalable models and systems that enhance clinical decision-making, optimize operational workflows, and deliver meaningful insights from complex healthcare data.
Career Level - IC3
What You’ll Do Modeling and Development: Fine-tune and evaluate large language models (LLMs), small language models, and retrieval-augmented generation (RAG) pipelines. Contribute to the design and development of AI solutions for use cases like summarizing clinical documents, surfacing patient insights, and supporting care decisions. Use tools like LangChain or other modular AI frameworks to experiment with agentic behaviors in workflows. Evaluation and Optimization: Help build model evaluation frameworks focused on healthcare-specific performance, semantic accuracy, and safety. Analyze model performance and iterate based on feedback and evaluation results. Collaboration and Integration: Work with product, engineering, and design teams to bring your models into Oracle's healthcare and life sciences platforms. Support integration of models into secure and compliant healthcare environments. Innovation and Learning: Stay up to date with recent developments in generative AI and NLP, especially in healthcare and life sciences. Propose and prototype new ideas that could lead to better healthcare tools and experiences. What You’ll Bring Education: PhD in Computer Science, NLP, Machine Learning, or a related field; OR Master’s degree with 4+ years of relevant experience in applied AI/ML. Experience: Experience training or fine-tuning LLMs or small language models. Experience in developing and evaluating LLM Agents for real-world problems Familiarity with retrieval-augmented generation (RAG), LangChain, or similar tools. Hands-on experience applying AI/ML in healthcare and/or bioinformatics is a plus. Skills: Strong understanding of machine learning, NLP, and deep learning techniques. Comfortable working with Python, TensorFlow/PyTorch, and open-source LLM tools. Familiarity with bioinformatics resources and tools Good communication skills and ability to collaborate across technical teams. Minimum Qualifications: PhD Computer Science, Mathematics, Statistics, Physics, Linguistics or a related field with a dissertation, thesis or final project centered in Machine Learning Techniques OR Masters or Bachelor's in one or more of these fields.
Minimum 2 years work experience in the areas of machine learning, computer vision, natural language processing or data mining with a PhD OR 4 years experience with a Master’s or Bachelor's.
Preferred Qualifications: Demonstrated experience in the areas of machine learning, computer vision, natural language processing or data mining.
Deep knowledge of algorithms and building models to deploy into production.
Experience with optimization, approximation algorithms, distributed algorithm design, and hands-on implementation of these techniques.
Implement production grade algorithms with inclusion of best practices in ML engineering.
Experience in research, data science or engineering around build and shipping machine learning or statistical models.
Proficient in designing and developing advanced ML models to solve diverse challenges and opportunities.
Strong understanding of modern machine learning techniques and their mathematical concepts.
Proficiency in at least one programming language.
Proficiency in at least one scripting language.
Training machine learning models with large scale data using techniques such as data and model parallelism.
Experience should include shipping machine learning or statistical models.
Publications at top-tier peer-reviewed conferences or journals.
Hands on experience in applicable programming languages in a production service environment.
Depending on the job there may be additional minimum requirements and/or preferred qualifications.