Oracle Cloud Infrastructure's Generative AI Service team builds advanced AI solutions for global, real-world challenges. This Principal Applied Data Scientist role focuses on leading the design and delivery of next-generation Generative AI and Machine Learning solutions for strategic customers, leveraging cutting-edge technology and Oracle's enterprise-scale cloud.
Key Responsibilities
- Design, build, and deploy cutting-edge machine learning and generative AI systems, focusing on Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG), and large-scale search.
- Collaborate with scientists, engineers, and product teams to turn complex problems into scalable, cloud-ready AI solutions for enterprises.
- Develop models and services for decision support, anomaly detection, forecasting, recommendations, NLP/NLU, speech recognition, time series, and computer vision.
- Run experiments, explore new algorithms, and push the boundaries of AI to optimize performance, customer experience, and business outcomes.
- Ensure ethical and responsible AI practices in all solutions.
- Lead and mentor teams from concept to delivery, driving product quality and innovation.
- Design and implement high-quality code for experiments and production ML models.
- Partner closely with customers to understand their vision, define requirements, and deliver AI solutions that remove blockers and unlock value.
- Dive deep into model architectures to maximize performance, scalability, and reliability.
- Configure and optimize large-scale OpenSearch clusters, including ingestion pipelines for high-volume data.
- Diagnose and resolve challenges in AI model training, deployment, and serving.
- Create reusable solution patterns and reference architectures that accelerate adoption across multiple customers.
- Act as a product evangelist showcasing innovations at customer meetings, industry events, and conferences.
- Conduct independent R&D to advance state-of-the-art ML with a focus on fairness and explainability.
Qualifications
- Bachelor's or Master's degree in Computer Science or related technical field, with 10+ years of experience in AI, ML, or data-driven solution development.
- Proven track record designing, building, and deploying scalable AI/ML solutions in production environments.
- Deep expertise in Large Language Models (LLMs), Generative AI, Agentic solutions, and advanced ML techniques (fine-tuning, prompt engineering, model optimization).
- Strong experience with OpenSearch, vector databases, data ingestion pipelines, and large-scale search optimization.
- Skilled in diagnosing, troubleshooting, and resolving issues in AI model training and serving.
- Hands-on experience with NLP, NLU, RAG architectures, Agents, and modern AI frameworks (e.g., LangChain, LlamaIndex).
- Proficient in Python and shell scripting, with familiarity in deep learning frameworks (PyTorch, TensorFlow, JAX, or Transformers).
- Experience with popular model training and serving frameworks like KServe, KubeFlow, Triton etc.
- Excellent communication skills for translating complex technical concepts into clear proposals, designs, and presentations.
- Collaborative mindset with experience working closely with product managers, engineers, and customers.
- Ability to mentor and guide junior data scientists or ML engineers.
- Experience acting as a technical evangelist, presenting at conferences, customer briefings, or industry events.
- Role: Data Science & Applied ML/AI.
