Senior ML Engineer

At Oracle Cloud Infrastructure (OCI) , we’re reimagining how enterprise cloud operations work—and we want you to be part of it.

OCI is a hyperscale cloud platform where operations are central to customer success. To scale and stay ahead, we’re automating incident detection, diagnosis, and resolution —pushing the boundaries of AI and GenAI in cloud operations.

As an ML Engineer , you’ll design and build intelligent AI solutions that proactively manage cloud environments, enhance operational excellence, and deliver world-class customer experiences.

If you’re passionate about solving complex technical challenges and shaping the future of the autonomous cloud, this is your moment.

Key Responsibilities

Lead AI Agent Development : Drive the end-to-end design and development of AI agents tailored for cloud operations, ensuring scalability, reliability, and alignment with customer needs.

Tooling & Infrastructure : Architect and implement tools and frameworks that accelerate AI agent development, experimentation, deployment, and monitoring.

Model Assessment : Design and execute robust methodologies to evaluate agent performance, safety, and accuracy across diverse operational scenarios.

Meta Prompting Innovation : Develop advanced meta prompting techniques to dynamically adapt prompts and maximize LLM utility in varied, real-time operational contexts.

GenAI / LLM Integration : Integrate cutting-edge LLM technologies into OCI systems, leveraging fine-tuning, retrieval-augmented generation (RAG), and other advanced techniques.

Cross-Functional Collaboration : Partner with product, UX, and engineering teams to align technical solutions with business priorities and user experience.

Customer Engagement : Collaborate directly with enterprise customers to gather requirements, validate solutions, and ensure agent effectiveness in production environments.

Required Qualifications

Overall 5+ years with 2+ years of experience in Machine Learning Engineering, with hands-on experience in building AI agents and production-grade ML systems.

Proven expertise in large language models (LLMs), transformers, and GenAI technologies.

Demonstrated experience in prompt engineering and developing prompting strategies for LLM-based applications.

Demonstrated ability to evaluate and optimize AI agent performance in real-world, mission-critical environments.

Solid programming skills in Python and practical experience with ML frameworks such as PyTorch or TensorFlow.

Deep understanding of MLOps practices, including model deployment, scalability, observability, and lifecycle management.

Excellent problem-solving skills with a bias for action and execution.

Ability to convince technical leaders and executives.

Strong written and verbal communication skills, including direct collaboration with enterprise customers and cross org teams.

Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical field

Preferred Qualifications

Experience building AI assistants or conversational agents for enterprise applications.

Experience working with multi-agent systems, reinforcement learning, or autonomous decision-making frameworks.

Familiarity with LLM fine-tuning, RAG (Retrieval-Augmented Generation), or Vector Database integration.

Background in cloud operations, DevOps, or infrastructure monitoring domains.

Familiarity with Oracle Cloud Infrastructure or other major cloud platforms.

Contributions to open-source ML projects and / or Publications or patents in ML, NLP, or AI agent systems.

Career Level - IC3