GenAI PhD Applied Scientist

The Program

Intended for students graduating with their Doctorate degree by December 2025, or those who have graduated within 12 months of the start date. Our program is designed to enhance your overall learning experience, help build your network, and accelerate your opportunity to make an impact. Future success at Oracle depends on hiring world-class, early-in-career talent who are looking to power next-generation services and solutions.

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

The Team

At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world.

Oracle Generative AI Service is an exciting team within OCI, dedicated to delivering innovative services at the intersection of artificial intelligence and cloud infrastructure. In this team, you will build and operate massive-scale cloud services leveraging state-of-the-art machine learning technologies. We are committed to providing the best in cloud products to meet the needs of our customers who are tackling some of the world’s most challenging problems.

The Oracle Cloud infrastructure business is growing at an incredible 52% annually. This growth results from Oracle’s strong legacy in helping organizations worldwide tackle their most 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 is the world’s leading provider of business software, with a presence in over 175 countries. We are one of the biggest technology companies on the planet, using innovative emerging technologies to tackle real-world problems today. From advancing energy efficiency to reimagining online commerce, our work transforms the world of business, advances governments, powers nonprofits, and provides billions of people with tools to outpace change. For more information about Oracle (NYSE:ORCL), visit us at oracle.com.

Responsibilities

As a GenAI PhD Applied Scientist in the Generative AI Service team, you will lead the effort of building distributed, scalable, high-performance AI model training and serving systems in partnership with our applied scientists and software engineers. You will dive deep into model structure to optimize performance and scalability, building state-of-the-art systems with cutting-edge technologies in this fast-evolving area. You will play a key role in shaping the future of Generative AI at Oracle, with an emphasis on Large Language Models (LLMs) and Multi-modality Models. Your contributions will be pivotal in delivering new Generative AI-powered services for large-scale enterprise customers.

• 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 global teams to drive projects from in-depth research to producing 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 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.
• 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, by December 2025.
• 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, 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.
• A background in Natural Language Processing and/or Computer Vision, Machine Learning, and Software Development, as well as experience in research and 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.
• Proven experience in designing data collection/annotation solutions and systematic evaluation necessary for developing and maintaining production systems.
• Commitment to staying up to date with the field and applying academic advances to solve complex business problems and bringing them into production.
• Strong publication record, including as a lead author or reviewer, in top-tier journals or conferences.
• Reside in the United States and/or attend a university in the US.
• Able to obtain work authorization in the US in 2025.

Preferred Qualifications:

• Knowledge of LLM and experience delivering Generative AI and Agent models are a significant plus.
• Familiarity and experience with the latest advancements in computer vision and multimodal modeling is a plus.
• 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
• Machine Learning
• Deep Learning
• Large Language Models
• PyTorch
• TensorFlow
• Natural Language Processing
• AI Architecture
• Distributed Systems
• Cloud Infrastructure