Principal Applied Scientist

Principal Applied Scientist at Oracle in Boise, Idaho, United States Job Description Job Description Building off our Cloud momentum, Oracle has formed a new organization - Oracle Health & AI. This team will focus on product development and product strategy for Oracle Health, while building out a complete platform supporting modernized, automated healthcare. This is a net new line of business, constructed with an entrepreneurial spirit that promotes an energetic and creative environment. We are unencumbered and will need your contribution to make it a world class engineering center with the focus on excellence. As our Principal Applied Scientist, you will play a key role in shaping the future of AI at Oracle, with an emphasis on Large Language Models (LLMs) and Generative AI. Your contributions will be pivotal in delivering our new Generative AI-powered solutions for healthcare and enterprise customers. Career Level - IC4 Responsibilities Responsibilities + Collaborate with product managers to translate business and product requirements into AI projects. + Collaborate with fellow technical leaders to ensure the successful and timely delivery of models and integration of services. + Coordinate with multinational teams to drive projects from research POC to production. + Develop new healthcare and enterprise services and features leveraging recent advances in generative AI, machine learning and deep learning. + Design and review the architecture of AI solutions, including data, model, training, and evaluation, employing best practices. + Lead and mentor both junior and senior applied scientists. + Develop production code and advocate for the best coding and engineering practices. + Participate in project planning, review, and retrospective sessions. + Identify and mitigate risks in our plans and executions, especially at the intersection of business and engineering. Qualifications and Experience + Demonstrated experience in designing and implementing scalable AI models for production. + Deep technical understanding of Machine Learning, Deep Learning architectures like Transformers, training methods, and optimizers. + Practical experience with the latest technologies in LLM and generative AI, such as parameter-efficient fine-tuning, instruction fine-tuning, and advanced prompt engineering techniques like Tree-of-Thoughts. + Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc. + Proven experi To view full details and how to apply, please login or create a Job Seeker account