Machine Learning Engineer

Job Description Oracle Health AI (OHAI) is at the forefront of transforming healthcare through advanced artificial intelligence and machine learning technologies. Our mission is to leverage Oracle’s leading cloud infrastructure, data assets, and deep healthcare expertise to create intelligent solutions that improve patient outcomes, streamline clinical workflows, and empower healthcare organizations worldwide. By integrating generative AI with robust data platforms, OHAI is building next-generation products that enable smarter, faster, and more personalized healthcare experiences - for providers, payers, and patients alike. Join us on our journey to bring cutting-edge technology to some of the world’s most meaningful and impactful challenges in healthcare. Qualifications and Experience :  3-5 or 5+ years of experience working as a machine learning engineer delivering products in real world applications.   Demonstrated experience in designing and implementing scalable ML solutions, frameworks and pipelines for production.   Demonstrated experience in architecture design, deployment/monitoring, API and service engineering, workflow and tooling development.  Demonstrated experience in leveraging LLMs (such as code assist) to accelerate the above development activities.  Good technical understanding of Large Language Model, Machine Learning / Deep Learning architectures like Transformers, training methods, and optimizers.  Proven experience in coaching teams on engineering practices and PR reviews.  Commitment to staying up to date with the field and applying latest technologies to solve complex business problems and bringing them into production.  Preferred Qualifications:    Knowledge of healthcare and experience delivering healthcare AI products are a significant plus.  Having referrable products delivered before is a significant plus.  Education :  Masters or bachelor’s in computer science or related field with 3-5 or 5+ years relevant experience  Responsibilities Responsibilities :  AI Product Development: Partner with product managers to translate business and healthcare requirements into actionable AI projects. Technical Leadership: Collaborate with technical leaders and multinational AI teams to deliver high-impact features and services on schedule. Cross-Functional Collaboration: Engage with both internal medical experts and customers to deeply understand healthcare contexts and inform AI solution development. Project Delivery: Drive projects from concept to production, participating in planning, review, and retrospective meetings. System Architecture and Infrastructure : Design and build scalable systems to support data processing, training, and deployment of generative AI models, while efficiently managing compute resources. Deployment and Monitoring : Automate deployment of generative models to production and set up monitoring to track their performance, reliability, and operational health. API and Service Engineering : Develop performant, secure APIs and services that enable seamless integration and scalable access to generative AI model capabilities. Development Workflow and Tooling : Create tools and workflows that ensure experiment reproducibility, dataset management, and smooth collaboration throughout the model lifecycle. Software Engineering Best Practices : Apply software engineering standards - such as modular code, testing, and documentation - to ensure maintainability and stability of ML systems. Hands-on Programming and Code Review : Perform day to day programming task, deliver production quality codes, do PR reviews and set bars for PR review process, advocating for maintainability and robustness. Mentorship: Lead and mentor both junior and senior applied scientists, fostering growth and technical excellence. Qualifications Career Level - IC4