Senior/Principal Applied Scientist
Key Skills for This Role
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Responsibilities:
- Lead the architectural design of AI solutions, ensuring scalability, reliability, and performance across complex projects.
- Oversee and guide projects from inception to delivery, managing all aspects of the project lifecycle to ensure successful outcomes.
- Make strategic decisions that shape the direction of AI projects, contributing to key decisions that are visible to and impact executives.
- Work alongside fellow technical leaders to ensure the seamless and timely delivery of sophisticated models, while ensuring their successful integration into our cutting-edge services.
- Coordinate with diverse, multinational teams to drive the projects from initial research and proof of concept to full-scale production, ensuring global impact.
- Leverage the latest breakthroughs in generative AI, machine learning, and deep learning to create innovative healthcare services and applications that set new industry standards.
- Design and review AI solutions with a focus on excellence, employing best practices for data management, model development, and evaluation to ensure the highest quality outcomes.
- Lead and mentor a talented team of both junior and senior applied scientists, fostering growth and nurturing the next generation of AI leaders.
- Develop production-level code while advocating for the best coding and engineering practices, ensuring robust and scalable AI solutions.
- Actively participate in project planning, review, and retrospective sessions, driving continuous improvement and strategic alignment.
- Identify potential risks at the critical intersection of business and engineering, and take proactive measures to ensure our plans and executions stay on track.
- Qualifications and Experience:
- Demonstrated experience in designing and deploying scalable AI models for production, with a track record of success in real-world applications.
- Proven experience in leading AI projects from conception to deployment, with a strong track record of delivering innovative solutions that meet business objectives.
- Demonstrated ability to manage cross-functional teams, including data scientists, engineers, and stakeholders, to ensure the successful execution of AI initiatives.
- Expertise in translating complex technical concepts into actionable strategies, ensuring alignment with organizational goals and timelines.
- Exceptional problem-solving skills with the ability to navigate challenges and adapt strategies in fast-paced, evolving environments.
- 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, showcasing your ability to stay at the forefront of AI technology.
- A strong commitment to staying current with the latest advancements in the field, applying cutting-edge academic research to solve complex business challenges, and successfully bringing innovative solutions into production.
- A robust publication record, including lead authorship in top-tier journals or conferences, demonstrating thought leadership and a deep understanding of AI research.
- Proven experience in leading and mentoring both senior scientists and early-career researchers, fostering a collaborative and innovative team environment.
- Eligibility to work in Australia without sponsorship
Preferred Qualifications:
- Knowledge of the healthcare domain and experience in delivering AI models specifically for healthcare applications is highly desirable.
- Familiarity with the latest advancements in computer vision and multimodal modelling is a valuable plus.
- Education:
- 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 5+ years of relevant experience is also considered.
- Oracle is committed to incorporating generative AI into our applications and workflows for business users. This role presents a unique opportunity to work on pioneering AI technologies and contribute to Oracle's Generative AI strategy. At Oracle, we value diversity and encourage continuous learning for career growth. Come join our team to make a significant difference!
About CLBPTS - All Lines of Business
Cloud infrastructure and enterprise software solutions provider.
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