GenAI PhD Applied Scientist

GenAI PhD Applied Scientist at Oracle

Intended for students graduating with their Doctorate degree by December 2025, or have graduated within 12 months of start date.

This position is fully in office, in our Austin, Nashville, Santa Clara, or Seattle Hub.

The Program

Oracle's future success hinges on world-class, early-career talent ready to power next-generation services and solutions. This program is designed to enhance your learning, expand your professional network, and accelerate your impact within the company.

The Team: Oracle Generative AI Service

At Oracle Cloud Infrastructure (OCI), we're a diverse team of creators and inventors building the future of cloud for Enterprises. We operate with the agility of a startup, backed by the scale and customer-focus of a global enterprise software leader.

The Oracle Generative AI Service team delivers innovative services at the intersection of artificial intelligence and cloud infrastructure. You will be building and operating massive-scale cloud services leveraging state-of-the-art machine learning technologies, committed to providing the best cloud products for customers tackling challenging problems.

Oracle Cloud Infrastructure is experiencing incredible annual growth (52%), driven by Oracle's legacy in solving complex challenges and its reputation for performance, reliability, and security.

Join an outstanding team of researchers to advance the state-of-the-art in areas such as:

• Generative AI Applications
• Agentic Platforms
• Reasoning and Planning
• Retrieval Augmented Generation
• Generative AI Evaluation
• Responsible AI
• Models’ Verticalization
• NL2Code, NL2SQL
• Multimodal GenAI
• Speech

The Company: Oracle

Oracle is the world’s leading provider of business software, present in over 175 countries and one of the largest technology companies globally. We use innovative emerging technologies to solve real-world problems, transforming business, advancing governments, powering nonprofits, and empowering billions. Learn more at oracle.com.

Responsibilities: What You’ll Do as a GenAI PhD Applied Scientist

As an Applied Scientist in the Generative AI Service team, you will lead efforts in building distributed, scalable, high-performance AI model training and serving systems, collaborating with applied scientists and software engineers. You will deeply analyze model structures to optimize performance and scalability, developing state-of-the-art systems with cutting-edge technologies. You will play a pivotal role in shaping the future of Generative AI at Oracle, focusing on Large Language Models (LLMs) and Multi-modality Models, and delivering new Generative AI-powered services for large-scale enterprise customers.

• Collaborate with product managers to translate business and product requirements into AI projects.
• Work with fellow technical leaders to ensure successful and timely delivery of models and service integration.
• Coordinate with global teams to drive projects from in-depth research to production-ready code.
• Develop new OCI services and features leveraging recent advances in generative AI, machine learning, and deep learning.
• Design and review the architecture of generative AI, including data, model, training, and evaluation, employing best practices.
• Lead and mentor both junior and senior machine learning engineers.
• Develop production code and advocate for best coding and engineering practices.
• Participate in project planning, review, and retrospective sessions.
• Identify and mitigate risks at the intersection of business and engineering.
• Work closely with cross-functional teams to integrate evaluation capabilities, identify new opportunities for evaluation, and explore emerging technologies.

What You'll Bring: Objective Minimum Qualifications

• PhD in Computer Science, Mathematics, Statistics, Physics, Linguistics, or a related field with a dissertation, thesis, or final project centered in Machine Learning and Deep Learning, to be completed by December 2025 or within 12 months of start date.
• Strong programming skills in Python and experience with deep learning frameworks such as TensorFlow or PyTorch.
• 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, including 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: LangChain, LlamaIndex, VectorStores, Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc.
• Background in Natural Language Processing and/or Computer Vision, Machine Learning, and Software Development, with experience in research, development, collaboration, and innovation.
• Hands-on experience in one or more areas: ASR, TTS, S2S translation, conversational AI, or related NLP topics.
• Proven analytical and problem-solving abilities in AI/ML or speech/language processing domains.
• Demonstrated experience in designing data collection/annotation solutions and systematic evaluation for production systems.
• Commitment to staying updated with the field and applying academic advances to solve complex business problems.
• Strong publication record (lead author or reviewer) in top-tier journals or conferences.
• Reside in the United States and/or attend a university in the US.
• Ability to obtain work authorization in the US in 2025.

Preferred Qualifications

• Knowledge of LLM and experience delivering Generative AI and Agent models.
• Familiarity and experience with the latest advancements in computer vision and multimodal modeling.
• Strong understanding of machine learning algorithms and architectures.
• Open-source contributions to the AI/ML community.
• Minimum 3.0 GPA.

Key Skills/Competency

• Generative AI
• Large Language Models (LLMs)
• Deep Learning
• Machine Learning
• Python
• TensorFlow/PyTorch
• Natural Language Processing (NLP)
• Computer Vision
• Distributed Systems
• AI Architecture Design