Senior Applied Scientist

Oracle Health and AI (OHAI) is a division of Oracle that focuses on building cutting-edge AI technology, particularly Generative AI, for healthcare applications. They are pioneers in delivering industry-leading AI solutions, notably for the Oracle Clinical Digital Assistant.
Australia
Data
Senior Software Engineer
Contact Company
3+ years of experience
AI · Healthcare

Description For Senior Applied Scientist

At Oracle Health and AI (OHAI), we're not just building the future of healthcare applications—we're redefining it. Our diverse team of visionaries and innovators is at the forefront of cutting-edge AI technology, particularly Generative AI, where creativity meets precision. As pioneers in this space, we've consistently delivered industry-leading AI solutions, notably for the Oracle Clinical Digital Assistant, solidifying our reputation as trusted leaders in the field.

Now, as we expand rapidly, we're channelling our expertise into transformative Generative AI solutions that promise to revolutionize healthcare for millions. Operating within a dynamic, agile environment, we enjoy strong backing from senior leadership and have a clear, impactful mission. Our close partnership with Oracle Cerner enables us to directly influence patient care on a massive scale, driving real change.

As our Senior Applied Scientist, you'll be at the heart of this transformation, shaping the future of AI at OHAI. Your expertise in Large Language Models (LLMs) and Generative AI will be crucial in bringing our visionary solutions to life, delivering groundbreaking healthcare applications that will set new standards across the industry.

Career Level - IC3

Last updated 2 months ago

Responsibilities For Senior Applied Scientist

  • Innovate AI models and features using advanced ML, DL, and NLP techniques for our AI/Generative AI projects.
  • Collaborate with internal teams or external vendors to collect and curate high-quality data for training and testing AI models.
  • Define and implement sophisticated evaluation metrics to measure and analyze model performance.
  • Run experiments and optimize models through hyperparameter tuning to achieve peak performance.
  • Conduct quantitative and qualitative analysis, including error analysis and ablation studies, to enhance model development and data quality.
  • Prepare detailed reports with evidence-based insights to support strategic decision-making.
  • Work closely with team members to ensure successful and timely model delivery and service integration.
  • Develop innovative healthcare and enterprise services by leveraging the latest advancements in generative AI, machine learning, and deep learning.
  • Participate actively in project planning, review, and retrospective sessions.
  • Write production-grade code, advocate for best coding practices, and conduct peer reviews to maintain high engineering standards.

Requirements For Senior Applied Scientist

Python
  • Demonstrated experience in designing and deploying scalable AI models for production, with a track record of success in real-world applications.
  • Deep technical knowledge of Machine Learning and Deep Learning architectures, such as Transformers, training methodologies, and optimization techniques.
  • Hands-on experience with the latest advancements in Large Language Models (LLM) and generative AI, including parameter-efficient fine-tuning, instruction fine-tuning, advanced prompt engineering, and Agent technology.
  • Practical experience with emerging LLM frameworks and plugins such as LangChain, LlamaIndex, VectorStores, Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, and Guidance.
  • Proven experience in designing data collection and annotation solutions, as well as systematic evaluation processes crucial for developing and maintaining high-quality production systems.
  • A robust publication record, including lead authorship in top-tier journals or conferences, demonstrating thought leadership and a deep understanding of AI research.
  • A PhD in Computer Science, Mathematics, Statistics, Physics, Linguistics, or a related field, with a dissertation or final project focused on Machine Learning and Deep Learning, and 3+ years of relevant experience is preferred but not mandatory; OR
  • A Master's or Bachelor's degree in a related field with 3+ years of relevant experience is also considered.

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