Industrial AI Scientist: LLMs, RAG & Predictive Maintenance

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Singapore

On-site

SGD 120,000 - 180,000

Full time

14 days+

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Job summary

Yokogawa Singapore seeks a hands-on AI researcher/engineer to develop LLM, Generative AI, and Agentic AI solutions for chemical and process industries. You will design AI-powered apps using plant data, engineering knowledge, and maintenance records to improve decision making.

The role covers RAG systems, knowledge graphs, semantic search, and intelligent agents that integrate with enterprise systems, digital twins, and engineering tools to automate workflows and support operations.

Qualifications

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
Expertise in Python programming and using libraries for data processing, visualization, and model development, including pandas, numpy, scikit-learn, matplotlib, and seaborn
Proficient in API concepts and libraries, and experienced in utilizing them for testing and deployment, leveraging frameworks such as Flask, Django, or FastAPI
Familiar with databases (e.g., PostgreSQL, Minio) and SQL for data storage and retrieval

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