Senior AI Architect — Enterprise ML & Production Systems

Evonik; Selangor; Sur place; MYR 180 000 - 320 000; Plein temps

Résumé du poste

Evonik Malaysia is seeking an experienced AI engineer to lead enterprise-scale AI solutions, from conception to production. You will architect AI systems with end-to-end operationalization, governance, and secure design, collaborating with diverse teams across the organization.

Requirements include a decade of hands-on AI/ML experience, strong Python, cloud native platforms, and MLOps expertise. Knowledge of manufacturing or chemical processes and SAP/365 tools is a plus.

Qualifications

• 10 years of experience in AI engineering, ML, software engineering, or data science, with enterprise AI delivery.
• Hands-on in machine learning, deep learning, generative AI, LLMs, RAG, agentic AI, model evaluation and optimization.
• Strong understanding of AI systems architecture, cloud-native platforms, API-first integration, secure design, and AI ops.
• Advanced Python with SQL, APIs, microservices, Azure AI services, Databricks, Docker, Kubernetes, Git, CI/CD.
• Experience with MLOps, lifecycle management, governance, deployment pipelines, and cloud-native platform engineering.
• Knowledge of manufacturing/chemical processes, SAP BTP, Azure, LeanIX, Power Platform.

Responsabilités

• Lead enterprise-scale AI solutions from conception to production.
• Architect AI systems with end-to-end operationalization and governance.
• Collaborate across teams to implement secure, scalable AI platforms.
• Provide technical leadership in AI, ML, and data engineering contexts.

Connaissances

AI engineering experience

Python

ML/LLM production

MLOps

Azure cloud

APIs

Docker

Kubernetes

Azure DevOps

Azure ML

Databricks

Git

CI/CD

Outils

Docker

Kubernetes

Azure DevOps

Azure ML

Databricks

Git

CI/CD

Description du poste

Evonik Malaysia is seeking an experienced AI engineer to lead enterprise-scale AI solutions, from conception to production. You will architect AI systems with end-to-end operationalization, governance, and secure design, collaborating with diverse teams across the organization.

Requirements include a decade of hands-on AI/ML experience, strong Python, cloud native platforms, and MLOps expertise. Knowledge of manufacturing or chemical processes and SAP/365 tools is a plus.