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About the Role
Research and develop innovative LLM, Generative AI, and Agentic AI solutions for chemical and process industry applications. Design and build AI-powered applications that leverage plant data, engineering knowledge, maintenance records, and operational documentation to improve decision making. Develop and deploy Retrieval-Augmented Generation (RAG) systems, knowledge graphs, and semantic search solutions to enable contextualized engineering insights. Build and orchestrate intelligent agents capable of interacting with enterprise systems, industrial databases, digital twins, and engineering tools to automate workflows and support operations. Develop scalable, reliable, and secure AI solutions, ensuring effective deployment, monitoring, maintenance, and continuous improvement in production environments. Apply machine learning, deep learning, multimodal AI, and advanced analytics techniques to solve challenges related to predictive maintenance, anomaly detection, process optimization, and asset performance. Build data engineering pipelines for acquiring, cleaning, enriching, and contextualizing structured and unstructured industrial data. Collaborate with researchers, software engineers, process engineers, and business stakeholders globally to design, evaluate, and deliver AI solutions from concept through production deployment. Automate engineering and business processes using AI, APIs, scripting, and open-source technologies to improve efficiency, scalability, and knowledge management. Stay current with advancements in LLMs, Agentic AI, machine learning, industrial AI, and emerging technologies, continuously contributing new ideas and innovations to the organization.
Responsibilities
- Research and develop innovative LLM, Generative AI, and Agentic AI solutions for chemical and process industry applications
- Design and build AI-powered applications that leverage plant data, engineering knowledge, maintenance records, and operational documentation to improve decision making
- Develop and deploy Retrieval-Augmented Generation (RAG) systems, knowledge graphs, and semantic search solutions to enable contextualized engineering insights
- Build and orchestrate intelligent agents capable of interacting with enterprise systems, industrial databases, digital twins, and engineering tools to automate workflows and support operations
- Develop scalable, reliable, and secure AI solutions, ensuring effective deployment, monitoring, maintenance, and continuous improvement in production environments
- Apply machine learning, deep learning, multimodal AI, and advanced analytics techniques to solve challenges related to predictive maintenance, anomaly detection, process optimization, and asset performance
- Build data engineering pipelines for acquiring, cleaning, enriching, and contextualizing structured and unstructured industrial data
- Collaborate with researchers, software engineers, process engineers, and business stakeholders globally to design, evaluate, and deliver AI solutions from concept through production deployment
- Automate engineering and business processes using AI, APIs, scripting, and open-source technologies to improve efficiency, scalability, and knowledge management
- Stay current with advancements in LLMs, Agentic AI, machine learning, industrial AI, and emerging technologies, continuously contributing new ideas and innovations to the organization
Requirements
- Masters/Degree in Engineering/Sciences
- 3-6 years of relevant experience
- Experience with knowledge graphs, semantic search, industrial digital twins, or engineering knowledge management systems
- Experience applying AI to plant operations, sustainability, energy optimization, asset performance management, or process safety use cases
- Familiarity with Responsible AI, AI governance, cybersecurity, and human-in-the-loop decision-support systems
- Experience in real-world data science projects, internships, hackathons, and personal projects
Skills
- Python programming
- pandas
- numpy
- scikit-learn
- matplotlib
- seaborn
- API concepts
- Flask
- Django
- FastAPI
- Databases (e.g., PostgreSQL, Minio)
- SQL
Experience Level
- 3-6 years
Education Level
- Masters/Degree in Engineering/Sciences
About the Company
- Yokogawa is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries.
- Yokogawa aims to shape a better future for our planet through supporting the energy transition, (bio)technology, artificial intelligence, industrial cybersecurity, etc.
- Yokogawa is committed to the United Nations sustainable development goals by utilizing its ability to measure and connect.
- Yokogawa has 18,000 employees working in over 60 countries with one corporate mission, to 'co-innovate tomorrow'.
- Yokogawa offers 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.
Equal Opportunity
- Yokogawa is an Equal Opportunity Employer.
- Yokogawa wants a diverse, equitable and inclusive culture.
- Yokogawa 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.
- Yokogawa 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.