Senior Applied Scientist - AI Innovation

Job Description Are you ready to join Oracle Analytics and help us revolutionize enterprise AI? We are on the lookout for a talented Senior Applied Scientist who will leverage their expertise in data management and enterprise software to drive innovations in agentic AI, generative AI, and state-of-the-art machine learning techniques. If you are passionate about learning from human feedback (LFHF) and user preference modeling, particularly within in-context learning and post-training methods for large language models, we want to connect with you! In this exciting role, you will have the opportunity to: Design and implement cutting-edge LFHF programs, fostering collaboration across product, UX, and data engineering teams, while developing robust annotation standards and quality controls. Create advanced preference and reward models utilizing pairwise and listwise techniques to enhance data efficiency. Build efficient post-training pipelines that improve model quality and performance through methods such as supervised fine-tuning (SFT) and reinforcement learning (RLHF/RLAIF). Innovate in-context learning approaches to tackle dynamic prompting and adherence to instructions. Enhance the AI infrastructure for scalable and compliant solutions, ensuring high-quality user experiences. Conduct thorough evaluations using both offline and online metrics, employing A/B testing to measure and monitor performance impacts effectively. Collaborate with cross-functional teams to ensure successful deployment of models in production while maintaining continuous operational quality. Minimum Qualifications Master's or PhD in Computer Science, Machine Learning, Statistics, Electrical Engineering, or a related field. Demonstrated experience in developing and deploying machine learning systems, especially focused on LLM post-training and assessment. Solid foundation in LFHF methodologies, with an emphasis on data design and preference modeling strategies. Proficiency in Python and familiarity with modern ML frameworks like PyTorch and Transformers. Published research in prestigious conferences such as NeurIPS, ICML, and ACL. Preferred Qualifications Experience in creating scalable data pipelines for feedback collection and active learning initiatives. Knowledge of causal inference and policy evaluation techniques. Understanding of LLM efficiency optimizations and safe AI practices. Exceptional communication skills, with the ability to convey complex topics to diverse audiences, and collaborate effectively across disciplines. Experience with experiment tracking and management of the machine learning lifecycle. Location: This position is located at Oracle's headquarters, with a flexible work schedule. The compensation for this role ranges from $97,500 to $199,500 per annum, with additional opportunities for bonuses and equity. About Us At Oracle, we are dedicated to delivering groundbreaking cloud solutions and partnering with industry leaders to drive progress. We value inclusivity and strive for a balanced work-life culture, offering a comprehensive array of benefits and opportunities for community engagement. Oracle is an Equal Employment Opportunity Employer, committed to promoting diversity and accessibility in the workplace.

Created: 2026-03-04