Senior AI/ML Engineer

Job Description

We are looking for a Senior 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 Overview

You will be part of a Project Delivery team to:

• 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.

Knowledge/ Professional Skills (Technical knowledge or skills required to perform the job)

Programming & Frameworks

• Languages: Proficiency in Python and visual basic coding is essential.
• ML Libraries: Expert-level knowledge of Numpy, Pandas, Scikit-learn, TensorFlow, and Keras.

Data Engineering & Integration

• Experience integrating AI/ML solutions into existing industrial control systems and operational dashboards.

Requirements

• 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.