Principal ML Engineer

Role Overview: At Oracle Cloud Infrastructure (OCI), we are on a mission to revolutionize cloud infrastructure operations by leveraging cutting-edge AI systems. As an ML Engineer, you will play a crucial role in driving the transformation of cloud operations at OCI. Your primary responsibility will be to develop intelligent AI solutions that proactively manage cloud environments, enhance operational excellence, and elevate the overall customer experience. This is a unique opportunity for you to tackle deep technical challenges and contribute to shaping the future of autonomous cloud technology. Key Responsibilities: - Lead AI Agent Development: Take charge of designing and developing AI agents specifically tailored for cloud operations, ensuring scalability, reliability, and alignment with customer requirements. - Tooling & Infrastructure: Architect and implement tools and frameworks to streamline AI agent development, experimentation, deployment, and monitoring processes. - Model Assessment: Design and execute methodologies to evaluate the performance, safety, and accuracy of AI agents across various operational scenarios. - Meta Prompting Innovation: Develop advanced meta prompting techniques to dynamically adjust prompts and maximize the utility of large language models (LLMs) in real-time operational contexts. - GenAI/LLM Integration: Integrate state-of-the-art LLM technologies into OCI systems, utilizing fine-tuning, retrieval-augmented generation (RAG), and other advanced techniques. - Cross-Functional Collaboration: Collaborate with product, UX, and engineering teams to align technical solutions with business priorities and enhance user experience. - Customer Engagement: Work closely with enterprise customers to gather requirements, validate solutions, and ensure the effectiveness of AI agents in production environments. - Technical Leadership: Mentor engineers, establish best practices in AI agent engineering, and contribute to the technical vision and roadmaps. Qualifications Required: - Minimum of 8 years of experience with at least 2 years in machine learning engineering, focusing on building AI agents and production-grade ML systems. - Expertise in large language models (LLMs), transformers, and GenAI technologies. - Proficiency in prompt engineering and developing strategies for LLM-based applications. - Ability to evaluate and optimize AI agent performance in real-world, mission-critical environments. - Strong programming skills in Python and hands-on experience with ML frameworks like PyTorch or TensorFlow. - Deep understanding of MLOps practices, including model deployment, scalability, observability, and lifecycle management. - Excellent problem-solving skills, with a proactive approach to execution. - Strong written and verbal communication skills for effective collaboration with enterprise customers and cross-organizational teams. - Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field. (Note: Preferred Qualifications and Additional Company Details sections are omitted as they were not provided in the job description),