Sr. Principal Applied Scientist- AI

Oracle Oracle · Enterprise · United States

Develop and deploy AI-driven applications using advanced Machine Learning and Agentic Workflows, focusing on LLM, RAG, and AI Agents for enterprise customers. This role involves building context layers, semantic foundations, evaluation solutions, and integrating with Oracle GenAI products, with a strong emphasis on productionizing AI/ML systems.

What you'd actually do

  1. Develop STOA agent context layers, semantic and knowledge foundations to enable enterprise level AI agent reasoning qualities.
  2. Develop STOA LLM, RAG and agent evaluation solutions and integrate with Oracle GenAI products.
  3. Develop algorithms and solutions using Reinforcement learning, Adversarial Generation and other data augment techniques for auto-evaluation.
  4. Design, develop, and deploy AI-driven applications using advanced Machine Learning and Agentic Workflows.
  5. Implement Retrieval-Augmented Generation (RAG) architectures and AI Agents for intelligent automation and decision-making.

Skills

Required

  • Python
  • Machine Learning
  • AI
  • Statistics
  • Algorithms
  • Large scale distributed systems
  • High-performance systems
  • Agentic Workflows
  • AI Agents
  • RAG architectures
  • Knowledge graphs
  • Ontologies
  • Semantic layers
  • Reinforcement learning
  • Adversarial Generation
  • Data augmentation
  • Retrieval-Augmented Generation (RAG)
  • Oracle Vector Database

Nice to have

  • Crew.ai
  • Langchain
  • Vector databases
  • Hyperscalers (AWS, Azure, GCP, OCI)
  • Ph.D. degree in AI/ML or statistics
  • building 0-1 products

What the JD emphasized

  • Minimal 10 years of related experience
  • Master’s degree in computer science, statistics, or machine learning. Ph.D. degree in AI/ML or statistics preferred.
  • Real-world experiences in productionizing AI/ML systems and AI/ML model development life cycles.
  • Strong expertise in Machine Learning/AI, Statistics, and Algorithms
  • Strong expertise in large scale distributed or high-performance systems.
  • Deep understanding of Agentic Workflows, AI Agents, or RAG architectures.
  • Deep understanding and hands on experience on building knowledge graphs, ontologies, and semantic layers.
  • Experiences with building 0-1 products are highly preferred.

Other signals

  • AI Agents
  • RAG
  • LLM applications
  • Enterprise scale AI