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We are looking for an AI/ML Engineer with deep technical expertise and proven leadership in delivering impactful solutions for the oil & gas industry. In this role, you will drive the design, development, and implementation of advanced AI/ML models, working closely with cross-functional teams to optimize operations and deliver data-driven insights in challenging industrial environments.
Job Responsibility:
Develop dynamic process simulation model to simulate various plant scenarios
Exploratory Data Analysis to analyze trends and patterns, data pre-processing and make intelligent recommendations
Implement classical machine learning techniques to prepare soft sensors, reinforcement learning models for process plant autonomous control operations
Design and develop AI models that troubleshoot the plant upsets, support asset performance management across various maintenance strategies
Leverage Generative AI (Large Language Models, Deep Reinforcement Learning) to enable multi-agent systems for collaborative decision-making and autonomous goal-seeking behavior
Ensure AI models are scalable and deployable within industrial platforms, integrating with PLC, DCS, SCADA, Historians, EAM, MES/MOM, SCM, and ERP systems
Ensure compliance with ethical AI principles, particularly in terms of fairness, transparency, and bias mitigation
Lead project implementation from data ingestion and feature engineering to model deployment and monitoring
Lead and mentor a team of process engineers and machine learning engineers
Review the process model and guide the team to develop plant scenarios in the dynamic simulation model accurately
Advocate best practices in Data analysis, Data pre-processing and machine learning model development
Partner with domain experts, process engineers, and project managers to translate complex operational challenges into AI-driven solutions
Present technical outcomes to both technical and non-technical audiences, highlighting business value and ROI
Ensure all AI/ML solutions comply with industry regulations, safety standards, and data governance policies
Proactively address potential risks related to data privacy, model bias, and operational safety
Requirements:
Bachelor’s/master’s in chemical engineering, AI, Machine Learning, or related field
10+ years of hands-on experience in AI/ML, with at least 4 years in a senior or lead role
Proven project delivery experience in industrial or energy sectors, with a preference for oil & gas
Demonstrated knowledge of oil & gas processes (upstream, midstream, downstream), instrumentation, and control systems
Proven Expertise to develop process dynamic simulations using PFDs and P&IDs and trouble shooting
Proficiency in handling large-scale data, time-series data, and sensor/IoT data within industrial contexts
Familiarity with real-time data challenges and solutions specific to high-stakes industrial environments
Strong foundation in machine learning algorithms (supervised, unsupervised, reinforcement learning), statistical modelling, and optimization techniques
Strong experience with classical machine learning, deep learning and reinforcement learning projects
Identify relevant metrics for A.I. model evaluation and Present technical outcomes to both technical and non-technical audiences, highlighting business value and ROI
Proven experience in Generative AI, RAG and vector embeddings for optimized knowledge retrieval and decision-making, and multi-agent systems for industrial applications
Expertise in cloud-based AI deployments (AWS, Azure, or Google Cloud) and edge AI for real-time decision-making
Strong analytical, problem-solving, and communication skills, with a proven ability to work across teams
Proficiency in Python and visual basic coding is essential
Expert-level knowledge of Numpy, Pandas, Scikit-learn, TensorFlow, and Keras
Experience integrating AI/ML solutions into existing industrial control systems and operational dashboards