Industrial AI Product Engineer - AI in Manufacturing

Evonik; Singapore; Presencial; SGD 120 000 - 180 000; Tempo integral

Resumo da oferta

Evonik (SEA) Pte. Ltd. is seeking a seasoned AI/ML professional to lead the deployment of AI-based solutions in industrial manufacturing.

You will own end-to-end AI projects from problem framing to integration into operational processes, while coaching teams in adopting AI capabilities across functions. The role emphasizes scaling production-grade ML/LLM systems, leveraging modern cloud architectures and Kubernetes, and collaborating with external partners within governance frameworks.

Qualificações

• Several years of experience in technical consulting and enabling AI-driven workflows in operational processes.
• Proven experience in productive use of modern ML and LLM-based approaches, including prompt engineering and agent-based systems.
• Solid understanding of ML/LLM models, lifecycle, validation, and limitations, plus knowledge of modern cloud architectures.

Responsabilidades

• Develop, implement, and deploy AI-based solutions into production within industrial manufacturing environments.
• Conduct data- and model-driven analyses to identify and implement optimization potential.
• Own AI projects from problem definition to integration into operational processes.
• Advance existing solutions and design new AI methods, products, and technologies (R&D).
• Coach and enable employees in AI across the organization.

Conhecimentos

Python

Azure

Data analysis

ML/AI systems

Prompt engineering

Kubernetes

Infrastructure as Code

Ferramentas

Kubernetes

Terraform

Cloud architectures

Descrição da oferta de emprego

Evonik (SEA) Pte. Ltd. is seeking a seasoned AI/ML professional to lead the deployment of AI-based solutions in industrial manufacturing.

You will own end-to-end AI projects from problem framing to integration into operational processes, while coaching teams in adopting AI capabilities across functions. The role emphasizes scaling production-grade ML/LLM systems, leveraging modern cloud architectures and Kubernetes, and collaborating with external partners within governance frameworks.