Senior Principal Member of Technical Staff

About Oracle and OHAI
Building off our Cloud momentum, Oracle has formed a new organization - Oracle Health & AI. This team will focus on product development and product strategy for Oracle Health, while building out a complete platform supporting modernized, automated healthcare. This is a net new line of business, constructed with an entrepreneurial spirit that promotes an energetic and creative environment. We are unencumbered and will need your contribution to make it a world class engineering center with the focus on excellence.
About ODA
Within the larger Oracle Health & AI organization, the Oracle Digital Assistant (ODA) is an Assistant platform that enables developers to create their own skills and digital assistants using the Conversational AI and Generative AI capabilities exposed to them in a low-code paradigm. The ODA team has been powering conversational AI experiences for all internal Oracle teams and several external customers for the past 7 years and is evolving rapidly to provide Generative AI solutions for the healthcare and enterprise domains. We operate in an agile environment with a substantial charter, high visibility, and support from senior leadership.
About the team
We are looking for ML scientists, Data Engineers, Software Development Engineers, Product/Program Managers and ML engineers with a strong background in machine learning to build industry-leading solutions. You will work with huge volumes of data to solve/enable solving real-world problems in the Healthcare domain that are productionized into our Health AI products. Your solutions will be productized as features in the end products. These are new teams that we are putting together in India Center from scratch and the work will span across New Feature Development for CDA Specialty Expansion & Innovation, Language & Region Expansion, Software Development across front-end, back-end, test automation and mobile, ML Engineering, MLOps, LLMOps, Applied ML Sciences and ML Research, with a huge focus on GenAI capabilities. There is a huge emphasis on Large Language Models (LLMs) and Generative AI. Your contributions will be pivotal in delivering our new Generative AI-powered solutions for healthcare and enterprise customers.

Qualifications
Ph.D. Degree preferred. 
Experience having led multiple projects leveraging LLMs, GenAI and Prompt Engineering Exposure to real-world MLOps deploying models into production adding features to products
Knowledge of working in a cloud environment
5+ Years of Experience
Strong understanding of LLMs, GenAI, Prompt Engineering and Copilot
 

Career Level - IC4

• The ML Engineer is expected to fully own the services that are built with the ML Scientists. This cuts across scalability, availability, having the metrics in place, alarms/alerts in place – and be responsible for the latency of the services
• Cloud Administration: administration of VMs and the cloud admin stuff including patching VMs, upgrading packages, working with endpoints, load balancing etc.; Production support of models managing incidents related to the models & data
• Setup CI/CD pipelines for the ML scientists and own the production pipeline around pushing things to prod; Setup and own MLOps environment around cloud
• Data quality checks & onboarding the data on to the cloud for modeling purposes
• Build extensible solutions around drift checks (model drift, data drift, concept drift), production quality code and impact assessment
• These roles should have a ML Sciences understanding as well
• Prompt Engineering, FT work, Evaluation, Data
• End-end AI Solution architecture, latency tradeoffs, LLM Inference Optimization, Control Plane, Data Plate, Platform Engineering
• Comfort in Python and Java is highly desirable
• The Senior Principal ML Engineer will head the ML engineering for a pod and be the technical leader for all ML/AI Engineering issues in a delivery pod

Responsibilities
 

• Collaborate with fellow technical leaders to ensure the successful and timely delivery of models from completion to production and integration of services
• Collaborate with product managers to ensure adoption plan and productization plan is part of the roadmap
• Ownership of the services encapsulating the ML models built by the scientists, working closely with them
• Coordinate with multinational teams to drive projects from research POC to production
• Design and review the architecture of AI solutions, including data, model, training, and evaluation, employing best practices
• Lead and mentor both junior and senior and Principal ML Engineers
• 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.
• Super-strong in Design and the signoff on the design for multiple delivery pods