Solutions Manager -AI & ML -Digitalization Project

Solutions Manager - AI & ML - Digitalization Project

Join to apply for the Solutions Manager - AI & ML - Digitalization Project role at Yokogawa

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 Purpose

• 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.
• Design and develop AI/ML models that support asset performance management across various maintenance strategies, including predictive, prescriptive, and cognitive maintenance.
• Implement analytical AI techniques (supervised/unsupervised learning, reinforcement learning) for predictive maintenance, defect elimination, and asset strategy optimization.
• Use AI/ML to analyze trends and patterns, make intelligent recommendations, and automate decision‑support systems.
• Develop intelligent recommendation systems that improve maintenance processes, criticality assessments, and reliability analytics.
• Ensure AI models are scalable and deployable within industrial platforms, integrating with DCS, PLC, SCADA, historians, EAM, MES/MOM, SCM, and SAP systems.
• Oversee the expansion of advanced automation and digital transformation solutions (AI/ML) and services into new asset developments and brownfield optimization projects across several industrial markets.

Key Responsibilities & Accountabilities

• Knowledge of software development processes and technical skills: lead the AI/ML engineering team to identify risks, propose solutions, and guide digital transformation solutions.
• Define the AI/ML strategy and roadmap for oil & gas solutions, aligning with Yokogawa’s digital transformation objectives.
• Architect end‑to‑end ML systems, from data ingestion and feature engineering to model deployment and monitoring.
• Understand customer business objectives and align Yokogawa capabilities and solutions to deliver measurable AI/ML outcomes.
• Lead and mentor a multidisciplinary team of data scientists, machine learning engineers, and software developers.
• Drive strategic initiatives to position AI/ML solutions for long‑term sustainability and profitability, establishing service orders and managing warranty & post‑delivery support for the U.A.E. business.
• Report to the Department Manager – Advanced Solutions on job progress, issues, resolutions, and manpower mapping for effective delivery.

Qualification And Experience

• A bachelor’s degree in data science, AI, or software engineering with a specialization in data science and strong process knowledge. Master’s degree is preferable.
• Minimum 15 years of experience.

Competencies

• Develop and optimize algorithms for real‑time analytics and predictive maintenance in upstream, midstream, and downstream operations.
• Perform model performance tuning to ensure reliability and scalability under production environments.
• Partner with domain experts, process engineers, and project managers to translate complex operational challenges into AI‑driven solutions.
• 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…