Senior ML Engineer

Oracle Cloud Infrastructure (OCI)

incident detection, diagnosis, and resolution

ML Engineer

this is your moment.

Key Responsibilities

Lead AI Agent Development:

Tooling & Infrastructure:

Model Assessment:

Meta Prompting Innovation:

GenAI/LLM Integration:

Cross-Functional Collaboration:

Customer Engagement:

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