Senior Applied Scientist

Oracle Analytics Cloud (OAC) is a market leading business analytics and business intelligence platform that delivers a full range of analytics and reporting capabilities.
Our Business Intelligence platform of products provides enterprise-class level performance, security, scalability and manageability as well as the very sophisticated and innovative features in core analytics.
The BI platform is a world-class federated database which enables business applications to query data from multiple heterogeneous systems and perform advanced business analytics.
OAC's application allows users to visualize, analyze, and explore data, as well as create consumable data products like interactive dashboards and reports.
OAC enables companies to quickly and accurately gain a holistic view of their performance, as well as optimize their decision-making process.
We have successfully differentiated ourselves from the competition by providing unparalleled breadth and depth in our features.
We are expanding our expertise in transformative Generative AI solutions that will revolutionize how customers interact with data.
As a Senior or Principal Applied Scientist, you will play a pivotal role in this transformation, shaping the future of AI at OAC.
Your deep expertise in Large Language Models (LLMs) and Generative AI will be essential in realizing our visionary solutions, driving innovative data analytics applications that set new industry benchmarks.
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Disclaimer: Oracle is an Equal Employment Opportunity Employer*.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law.
Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
* Which includes being a United States Affirmative Action Employer Oracle Analytics Cloud is looking for a Principal Applied Scientist with Generative AI expertise to build next-generation analytics experiences.
Responsibilities: Collaborate with product managers to translate business and product visions into innovative AI projects that push the limits of data analytics and business intelligence.
Work closely with technical leaders to ensure the seamless and timely delivery of advanced models, while guaranteeing their successful integration into our cutting-edge services.
Coordinate across diverse, multinational teams to drive projects from initial research and proof of concept to full-scale production, ensuring a broad global impact.
Leverage the latest advancements in generative AI & LLMs, machine learning, and deep learning to develop groundbreaking data analytics and business intelligence solutions that set new industry benchmarks.
Design and evaluate AI solutions with a focus on excellence, adhering to best practices in data management, model development, and evaluation to deliver high-quality results.
Lead and mentor a high-performing team of junior and senior applied scientists, fostering growth and shaping the next generation of AI leaders.
Write production-level code while promoting best practices in coding and engineering, ensuring scalable, robust AI solutions.
Take an active role in project planning, reviews, and retrospectives, driving continuous improvement and aligning projects with strategic objectives.
Proactively identify and mitigate risks at the critical intersection of business and engineering to keep plans and execution on track.
Required Qualifications: Proven experience in designing and deploying scalable AI models for production, with a strong track record of success in real-world applications.
In-depth technical expertise in Machine Learning, Deep Learning, and Generative AI architectures, including neural networks, transformers, encoders, and decoders.
Hands-on experience with the latest advancements in Large Language Models (LLMs) and generative AI, including parameter-efficient fine-tuning, instruction fine-tuning, advanced prompt engineering, and agent-based technologies.
Practical experience with emerging LLM frameworks and tools, such as LangChain, LlamaIndex, VectorStores, Retrievers, LLM Cache, and LLMOps (e.g., MLFlow), demonstrating your ability to stay at the cutting edge of AI technology.
Proven ability in designing data collection and annotation pipelines, along with systematic evaluation processes essential for building and maintaining high-quality production systems.
A strong commitment to staying up-to-date with the latest developments in AI, leveraging cutting-edge academic research to address complex business challenges and successfully deploying innovative solutions into production.
A robust publication record, including lead authorship in top-tier journals or conferences, reflecting thought leadership and deep expertise in AI research.
Preferred Qualifications: Knowledge of AI applications for data analytics and business intelligence is a plus.
Familiarity with advancements in Generative AI/LLMs, Agent technologies is highly desirable.
Education: A PhD or Postdoctoral experience in Computer Science, Mathematics, Statistics, Computational Linguistics, or a related field, with a dissertation or final project focused on Machine Learning and Deep Learning, Generative AI & LLMs.
A minimum of 6 years of relevant industry experience is expected.
#LI-DNI Responsibilities: Collaborate with product managers to translate business and product visions into innovative AI projects that push the limits of data analytics and business intelligence.
Work closely with technical leaders to ensure the seamless and timely delivery of advanced models, while guaranteeing their successful integration into our cutting-edge services.
Coordinate across diverse, multinational teams to drive projects from initial research and proof of concept to full-scale production, ensuring a broad global impact.
Leverage the latest advancements in generative AI & LLMs, machine learning, and deep learning to develop groundbreaking data analytics and business intelligence solutions that set new industry benchmarks.
Design and evaluate AI solutions with a focus on excellence, adhering to best practices in data management, model development, and evaluation to deliver high-quality results.
Lead and mentor a high-performing team of junior and senior applied scientists, fostering growth and shaping the next generation of AI leaders.
Write production-level code while promoting best practices in coding and engineering, ensuring scalable, robust AI solutions.
Take an active role in project planning, reviews, and retrospectives, driving continuous improvement and aligning projects with strategic objectives.
Proactively identify and mitigate risks at the critical intersection of business and engineering to keep plans and execution on track.
Required Qualifications: Proven experience in designing and deploying scalable AI models for production, with a strong track record of success in real-world applications.
In-depth technical expertise in Machine Learning, Deep Learning, and Generative AI architectures, including neural networks, transformers, encoders, and decoders.
Hands-on experience with the latest advancements in Large Language Models (LLMs) and generative AI, including parameter-efficient fine-tuning, instruction fine-tuning, advanced prompt engineering, and agent-based technologies.
Practical experience with emerging LLM frameworks and tools, such as LangChain, LlamaIndex, VectorStores, Retrievers, LLM Cache, and LLMOps (e.g., MLFlow), demonstrating your ability to stay at the cutting edge of AI technology.
Proven ability in designing data collection and annotation pipelines, along with systematic evaluation processes essential for building and maintaining high-quality production systems.
A strong commitment to staying up-to-date with the latest developments in AI, leveraging cutting-edge academic research to address complex business challenges and successfully deploying innovative solutions into production.
A robust publication record, including lead authorship in top-tier journals or conferences, reflecting thought leadership and deep expertise in AI research.
Preferred Qualifications: Knowledge of AI applications for data analytics and business intelligence is a plus.
Familiarity with advancements in Generative AI/LLMs, Agent technologies is highly desirable.
Education: A PhD or Postdoctoral experience in Computer Science, Mathematics, Statistics, Computational Linguistics, or a related field, with a dissertation or final project focused on Machine Learning and Deep Learning, Generative AI & LLMs.
A minimum of 6 years of relevant industry experience is expected.
#LI-DNI