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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 recommendations 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.
- To oversee the expansion of our advanced automation and digital transformation solutions (AI/ML) and services into new asset developments and brownfield optimization projects across several industrial markets
- Knowledge of software development process and technical skills: Lead AI /ML Engineer must know the technical aspects of projects to identify risks, propose immediate solutions and provide guidance for 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.
- The objective is to understand your customer’s business objectives to align with Yokogawa capabilities and solutions. In this role you will lead other Yokogawa key contributors in an overall strategy to implement solutions that will contribute to customer business objectives in a way that is meaningful and measurable in the areas of AI/ML solutions.
- Lead and mentor a multidisciplinary team of data scientists, machine learning engineers, and software developers.
- Make strategy, implement initiatives & measures to help position AI/ML solutions to achieve long term sustainability and profitability on establishing site services orders, management of warranty & post-delivery support for YUAE business.
- Report to Department Manager-Advanced Solutions Department on job progress, issues and resolutions and manpower-mapping for effective delivery of solution.
- Lead and mentor a multidisciplinary team of data scientists, machine learning engineers, and software developers.
- A bachelor’s degree in data science / AI or Software engineering with specialization in data science and having strong process knowledge. Master’s degree is preferable.
- Minimum 15 years of experience.
- 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 addresses potential risks related to data privacy, model bias, and operational safety.
- Capable of managing field surveys, designing automation functions, and ensuring compliance with project quality standards.
- Capable of overseeing multiple projects, ensuring the successful delivery of projects involving advanced automation technologies including AI/ML and managing all aspects of project execution
- Deep technical knowledge in process solutions and expertise in specialty Chemicals & Process, including understanding Chemical Properties, Manufacturing Processes, Operations and Industry-specific challenges
- Stay updated on the latest trends, technologies, and regulations in the specialty chemicals & Process industry and provide insights that influence product/service/solution development and strategic planning
- Customer Focus with Strategic Mindset
- Proven track record of field experience and technical skills
- Excellent verbal and written communication skills
- Good leadership skills
- Knowledge and experience in implementing AI /ML Project
- Knowledge in advanced level for programing in Python, C++, Java, C#, SQL, Matlab etc
- Strong experience with Predictive Analytics and Prescriptive Analytics using tools like TensorFlow, PyTorch, and familiarity Keras, XGBoost.
- Strong foundation in machine learning algorithms (supervised, unsupervised, reinforcement learning), statistical modelling, and optimization techniques.
- Proficiency in handling large-scale data, time-series data, and sensor/IoT data within industrial contexts.
- Expertise in cloud-based AI deployments (AWS, Azure, or Google Cloud) and edge AI for real-time decision-making.
- Hands-on experience with major cloud platforms (AWS, Azure, or GCP) for model deployment and data processing.
- Strong analytical, problem-solving, and communication skills, with a proven ability to work across teams.
- Familiarity with distributed data processing and big data technologies (Spark, Hadoop), plus knowledge of time-series databases (e.g., InfluxDB, OSIsoft PI) is an added advantage.
- Knowledge of working on DCS platforms.
- Consistently demonstrates exceptional technical skills, competence, and productivity.
- Possesses excellent communication and interpersonal abilities.
- This position is best filled by someone with a firm understanding and knowledge in AI /ML with data science background with having process Plant Operations -Onshore /Offshore/Refining -Upstream, Midstream & downstream with Process Automation/Process Control in both discrete and continuous manufacturing.
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