
Applied Scientist 5
- India
- Permanent
- Full-time
- Being part of one of the most visionary and mission-driven organizations in Oracle, cooperating with talented peers with diverse backgrounds worldwide.
- High visibility to senior leadership, as well as technical leaders and partners.
- Opportunity to build state-of-the-art technologies in large language models and generative AI at scale.
- Close partnership with product managers and software engineers to deploy Generative AI features into products in various business-critical scenarios.
- Building performance evaluations of Generative AI systems for continuous improvement of alignment with stakeholders' growing expectations.
- Develop, implement, and optimize large language models and generative AI technologies, including training/finetuning and computation optimizations.
- Collaborate with software engineers to deploy LLM / Generative AI models and Agents into production environments.
- Stay up-to-date with the latest advancements in the field of generative AI.
- Collaborate with cross-functional teams to drive the development and adoption of LLM and generative AI solutions across various organizations in the company.
- Work directly with key customers and accompany them on their AI journey - understanding their requirements, help them envision and design the right solutions and work together with their engineering and data science team to remove blockers and translate the feedback into actionable items for individual service owners.
- Design and build solutions and help GBU development teams reach successful pilots, PoCs and feature releases with our AI/Gen AI and DS technologies.
- Bring back learnings from these engagements to standardize Generative AI and Agent implementations for efficiency, scale and ease of maintenance.
- Support GBU consulting with re-usable solution patterns and reference solutions / showcases that can apply across multiple customers.
- Being enthusiastic, self-motivated, and a great collaborator. Lead patent filings and author papers to show innovative enterprise grade developments.
- Be our product evangelist - engage directly with customers and partners, participate and present in external events and conferences, etc.
- PhD, MS in computer science, engineering, mathematics or a field related to deep learning.
- Strong knowledge of ML fundamentals - supervised vs unsupervised modeling, time series, highly unbalanced and noisy data sets, complex feature engineering, recommendation systems, using and optimizing gradient boosting models, NLP, deep learning on all kinds of unstructured data.
- 5+ (for Senior), 7+ (for Principal), 10+ (for Sr Principal) years of work experience including a minimum of 2-year experience in developing large-scale ML solutions, and in particular deep learning solutions in the NLP field.
- Proficiency with deep learning frameworks (such as PyTorch or TensorFlow) and deep learning architectures (especially Transformers).
- Hands-on experience with distributed training of large language models.
- Strong development experience of deep learning modeling in Python.
- Familiarity with the latest advancements in LLM and generative AI technologies.
- Familiarity with engineering best practices, including shared codebase, version control, containerization, etc.
- Passionate about being a builder and working with talented peers to solve hard problems at scale.
- Good communication skills to convey technical concepts in straightforward terms with product managers and various stakeholders.
- Publications in top-tier deep learning conferences or significant contributions to prominent deep learning repositories
- Industrial experience in system design, software development, and production deployment
- Excel in transforming ambiguous requirements into actionable plans with deep learning techniques for problem-solving.
- First-hand experience with deep reinforcement learning
- First-hand experience with the latest technologies in LLM and generative AI such as parameter-efficient finetuning and instruction finetuning is a plus
- Familiarity with the latest advancements in computer vision and multimodal models is a plus
- Top-tier performance in prestigious deep learning leaderboards or large model-related competitions is a plus.