We are looking for an AI/ML Engineer for one of our clients with the following details:

Location: Bahrain

Start Date: Start Date: ASAP

Work status: Residential- single status

Qualification and Experience Required:

• 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.

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.

Personal Attributes (Special personal characteristics/ interpersonal skills)

• Consistently demonstrates exceptional technical skills, competence, and productivity.


• Deeply passionate about transforming emerging technologies into practical, industrial solutions.


• Possesses excellent communication and interpersonal abilities.


• A fast learner with a strong aptitude for collaboration and teamwork.

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 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.

Key Responsibilities

Technical Leadership & Mentorship

• I. 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.

Stakeholder Collaboration & Communication

• 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.

Compliance & Risk Management

• 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.

If Interested Kindly apply.