Principal Applied Scientist

Job Description

Oracle Cloud Infrastructure blends the speed of a startup with the scale of an enterprise leader. Our Generative AI Service team builds advanced AI solutions that run on powerful cloud infrastructure tackling real-world, global challenges.

In this role, you will:

- Design, build, and deploy cutting-edge machine learning and generative AI systems, with a focus 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.

We're looking for a Principal Applied Data Scientist with deep expertise in applied ML/AI, hands-on experience building production-grade solutions, and the creativity to innovate at the intersection of AI and enterprise cloud.

As a Principal Applied Data Scientist in Oracle's OCI Gen AI & AI Solutions Engineering team, you'll shape the future of enterprise AI for our most strategic customers. You'll lead the design and delivery of next-generation generative AI and machine learning solutions-leveraging cutting-edge technology and Oracle's enterprise-scale cloud to solve complex, high-impact problems in industries like finance, telecom, healthcare, and software development. 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. Collaborate with product and engineering teams to deliver customer-focused, market-differentiating AI solutions. Conduct independent R&D to advance state-of-the-art ML with a focus on fairness and explainability.

You will:

- 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.
- Build state-of-the-art solutions using emerging Gen AI and ML technologies.
- 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 our innovations at customer meetings, industry events, and conferences.
- Collaborate with world-class scientists, engineers, and product managers in a fast-moving, high-impact environment.

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.

Career Level - IC4

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