AI/ML Engineer (24/02/2026) Bahrain
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.