Oracle · 11 hours ago

GenAI PhD Applied Scientist - Oracle Cloud Infrastructure

United States

Full-time

Remote

Entry Level

$97K/yr - $200K/yr

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Data GovernanceData Management

No H1B

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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 global teams to drive projects from research to production.

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.

Qualification

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Related fieldMachine LearningDeep LearningGenerative AILLM frameworksTransformersAI model designData collection solutionsPublication recordProject planningCollaboration skillsMentoring skills

Required

Have a 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 August 2025.

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 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.