AI ML Engineer ADNOC | Online

Job Description: AI/ML Engineer (ADNOC 2026)

Are you ready to join the “Nervous System” of the world’s most advanced energy company? ADNOC is seeking AI/ML Engineers to drive its ENERGYai initiative—a first-of-its-kind agentic AI project designed to transform the global energy landscape from its headquarters in Abu Dhabi.

In this role, you will work at the core of ADNOC’s digital transformation. You won’t just be building models; you will be developing Agentic AI systems trained on petabytes of proprietary data to optimize everything from seismic interpretation to autonomous drilling. As ADNOC pivots from a traditional oil company to a foundational enabler of the global AI economy, you will be architecting the solutions that power this shift.

Your Technical & Industrial Mission

Energy-Specific AI Development

• Agentic AI (ENERGYai): Develop and scale “AI Agents” that can perceive, think, and act autonomously across the upstream and downstream value chains.

• Seismic & Subsurface Intelligence: Use Deep Learning to accelerate seismic interpretation by up to 10x, improving the precision of reservoir modeling and reducing exploration risks.

• Predictive Maintenance at Scale: Implement ML models across thousands of critical assets (compressors, pumps, and pipelines) to predict failures weeks in advance, potentially saving millions in unplanned downtime.

Advanced System Architecture

• Scalable MLOps: Design and manage production-grade pipelines that integrate with ADNOC’s Panorama Digital Command Center, ensuring models are resilient and real-time.

• Multi-Modal Data Fusion: Combine IoT sensor data, satellite imagery, and historical engineering logs to create a unified “Digital Twin” of ADNOC’s global operations.

• Hybrid Cloud Strategy: Utilize Azure and AWS alongside private 5G networks to deploy AI at the “edge”—directly on offshore platforms and remote oilfields.

What You Bring to ADNOC

• Education: Bachelor’s or Master’s in Computer Science, AI, or Data Science.

• Experience: 3–7 years of hands-on experience in an enterprise setting, ideally with exposure to heavy industry or energy sectors.

• Technical Mastery:

  • Languages: Expert Python and SQL; proficiency in R is a plus.

  • Frameworks: PyTorch, TensorFlow, Scikit-learn.

  • Infrastructure: Deep knowledge of MLOps, Kubernetes, and Cloud Platforms (Azure/AWS).

• Domain Interest: A passion for applying AI to solve sustainability challenges, such as carbon capture optimization and emission tracking.

Job Overview & Benefits