Senior AI/ML Engineer

Posted One Month Ago
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Hiring Remotely in Muharraq, BHR
Remote
Senior level
Hardware • Information Technology • Industrial • Automation
The Role
Lead design, development, and deployment of AI/ML solutions for industrial plants: build dynamic process simulations, perform EDA and pre-processing, implement classical and reinforcement learning models, apply generative AI and multi-agent systems, integrate models with control systems (PLC/DCS/SCADA) and enterprise systems, and ensure scalable, compliant, and safe production deployments.
Summary Generated by Built In

Not just a job, but a career

Yokogawa, award winner for ‘Best Asset Monitoring Technology’ and ‘Best Digital Twin Technology’ at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries. 

Our aim is to shape a better future for our planet through supporting the energy transition, (bio)technology, artificial intelligence, industrial cybersecurity, etc. We are committed to the United Nations sustainable development goals by utilizing our ability to measure and connect.

About the Team
Our 18,000 employees work in over 60 countries with one corporate mission, to "co-innovate tomorrow". We are looking for dynamic colleagues who share our passion for technology and care for our planet. In return, we offer you great career opportunities to grow yourself in a truly global culture where respect, value creation, collaboration, integrity, and gratitude are highly valued and exhibited in everything we do.

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.

Key Responsibilities

Technical Leadership & Mentorship

  • A.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.

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.

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.

Yokogawa is an Equal Opportunity Employer. Yokogawa wants a diverse, equitable and inclusive culture.  We will actively recruit, develop, and promote people from a variety of backgrounds who differ in terms of experience, knowledge, thinking styles, perspective, cultural background, and socioeconomic status.  We will not discriminate based on race, skin color, age, sex, gender identity and expression, sexual orientation, religion, belief, political opinion, nationality, ethnicity, place of origin, disability, family relations or any other circumstances.  Yokogawa values differences and enables everyone to belong, contribute, succeed, and demonstrate their full potential.

Are you being referred to one of our roles? If so, ask your connection at Yokogawa
about our Employee Referral process!

Skills Required

  • Bachelor's or Master's in Chemical Engineering, AI, Machine Learning, or related field
  • 10+ years hands-on AI/ML experience with at least 4 years in a senior or lead role
  • Proven project delivery experience in industrial or energy sectors
  • Preference for oil & gas domain experience
  • Demonstrated knowledge of oil & gas processes, instrumentation, and control systems
  • Expertise developing dynamic process simulations using PFDs and P&IDs and troubleshooting
  • Proficiency handling large-scale, time-series, and sensor/IoT data
  • Familiarity with real-time data challenges in high-stakes industrial environments
  • Strong foundation in supervised, unsupervised, and reinforcement learning, statistical modeling, and optimization
  • Proven experience in classical ML, deep learning, and reinforcement learning projects
  • Experience with Generative AI, RAG, vector embeddings, 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
  • Proficiency in Python and Visual Basic
  • Expert-level knowledge of Numpy, Pandas, Scikit-learn, TensorFlow, and Keras
  • Experience integrating AI/ML solutions into industrial control systems and operational dashboards
  • Strong analytical, problem-solving, and communication skills
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The Company
HQ: Mušyna
18,313 Employees
Year Founded: 1915

What We Do

Yokogawa Electric Corporation provides industrial automation, control, measurement, and information solutions for customers across energy, materials, life sciences, and other industries. Its offerings include distributed control systems, production-control software, pressure transmitters, process analyzers, programmable controllers, industrial recorders, and high-precision measuring instruments. The company also develops industrial IoT hardware, software, and cloud solutions, supported by engineering, project-management, and maintenance services for plant operators.

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