Artificial Intelligence Engineer

Job Summary We are looking for an experienced AI / Machine Learning Engineer with strong expertise in building and deploying AI solutions in production environments. The ideal candidate should have hands-on experience with Computational Knowledge Graphs , strong mathematical foundations, and practical exposure to machine learning, optimization techniques, and scalable system design. Experience working with Oil & Gas domain data and business processes is highly preferred.

Key Responsibilities Design, develop, deploy, and maintain AI/ML applications for production-scale environments. Build and optimize Computational Knowledge Graph solutions for intelligent data modeling and decision support. Develop machine learning models for prediction, classification, optimization, and analytics use cases.

Implement scalable AI architectures and integrate them with enterprise platforms. Work with structured and unstructured datasets to derive business insights. Design and optimize algorithms using mathematical and statistical techniques.

Develop APIs and backend services for AI model integration. Collaborate with cross-functional teams including data engineers, software developers, and business stakeholders. Apply AI solutions to solve business problems in the Oil & Gas domain.

Monitor model performance and continuously improve system reliability and efficiency. Follow MLOps and software engineering best practices for deployment and lifecycle management. Required Skills & Qualifications Technical Skills Strong proficiency in Python (mandatory) Good programming knowledge in Java, C++, TypeScript/JavaScript Strong mathematical foundations including: Linear Algebra Probability & Statistics Optimization Techniques Calculus (preferred) Solid understanding of: Machine Learning algorithms Deep Learning concepts Feature Engineering Model Evaluation & Optimization System Design principles Experience with Computational Knowledge Graphs / Graph-based AI systems Exposure to AI deployment and production-grade ML systems Experience with cloud platforms and scalable architecture is preferred Understanding of MLOps concepts and model lifecycle management