Principal Machine Learning Engineer

Oracle Cloud Infrastructure (OCI) is building the future of the cloud for Enterprises, and they are seeking a Principal Machine Learning Engineer. In this role, you will design and develop AI software, participate in the software lifecycle, and build cloud services while addressing challenges at the intersection of artificial intelligence and cloud infrastructure.

Responsibilities:

• Design and develop AI software in Java, Python, and other languages
• Participate in the entire software lifecycle – development, testing, CI/CD and production operations
• Participate in the entire model development cycle - training, fine-tuning, model serving, evaluation/benchmarking and human preference learning
• Apply engineering principles for defining robust and maintainable architectures and designs
• Build cloud service on top of the modern Infrastructure as Service (IaaS) building blocks at OCI
• Design and build distributed, scalable, fault tolerant software systems to facilitate development of GenAI models
• Identify requirements, scope solutions, estimate work, schedule deliverables. Help establish and drive the adoption of outstanding coding standards and patterns and help enhance our inclusive engineering culture
• Contribute to publications, blogs and open-source ML performance submissions partnering with product managers
• Balance between product feature development and production operational concerns like ops automation, structured logging, instrumentation for metrics and participating in on-call

Requirements:

• BS/MS in Computer Science or equivalent experience
• 6–10+ years building and shipping enterprise distributed or cloud-native systems
• Experience scaling heterogeneous CPU/GPU training infrastructure for large multimodal frontier models
• Strong foundation in system design, distributed systems, and cloud architecture best practices
• Proficiency in Java, Python, or similar object-oriented languages
• Experience building highly available services using service-oriented design patterns and service-to-service communication protocols
• Proven ability to deliver impact in collaborative, fast-paced environments
• Strong verbal and written communication skills, including technical design documentation
• Hands-on experience with containers and orchestration technologies such as Kubernetes and Docker
• Production experience with Cloud and ML technologies
• Experience working in the below areas and algorithms will be ideal but not mandatory: Generative AI Modeling: Customizing LLM's, build and deploy LLM's at scale for large scale data generation
• Algorithms: Transformer models, Attention mechanism, Prompt tooling