Principal Applied Scientist
Oracle
- Australia
- Permanent
- Full-time
- 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 multinational teams to drive projects from research POC to production.
- Develop new AI models and solutions leveraging recent advances in generative AI, machine learning and deep learning.
- Design and review the architecture of AI solutions, including data, model, training, and evaluation, employing best practices.
- Lead and mentor both junior and senior applied scientists.
- 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.
- Demonstrated experience in designing and implementing scalable AI or LLM models for production.
- Practical experience with the latest technologies in LLM and generative AI, such as instruction finetuning, preference fine-tuning, and advanced prompt engineering techniques.
- 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 LLM evaluation frameworks 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.
- Experienced leading senior scientists and early-career scientists.
- Knowledge or experience in developing models, evaluation systems, or datasets for LLM-based Agent is a significant plus.
- Knowledge or experience in LLM evaluation, LLM leaderboard, and LLM inference acceleration and optimization is a plus.
- PhD Computer Science, Mathematics, Statistics, Physics, Linguistics or a related field with a dissertation, thesis or final project centred in Machine Learning, Deep Learning, or Generative AI with 3+ years relevant experience is preferred but not a must; OR
- Masters or Bachelor's in related field with 5+ years relevant experience
- Which includes being a United States Affirmative Action Employer