MLOps (Machine Learning Operations) Tech Lead
Henkel AG & Co. KGaA1 day ago
Cairo, EgyptStaff+
Responsibilities
- Design, build, and maintain end-to-end MLOps and AI engineering platforms and solutions.
- Develop and optimize data and machine learning pipelines for model development and deployment.
- Implement automation, CI/CD pipelines, infrastructure-as-code, and reusable engineering frameworks.
- Establish best practices, standards, and governance mechanisms for AI engineering and model operations.
- Collaborate with data scientists, data engineers, architects, and business stakeholders to bring AI solutions into production.
- Monitor, troubleshoot, and improve the reliability, scalability, performance, and cost efficiency of AI systems and infrastructure.
- Evaluate and adopt emerging technologies in AI, MLOps, and cloud engineering.
Requirements
- Experience designing and operating end-to-end MLOps and AI engineering solutions.
- Experience developing data and machine learning pipelines using cloud and orchestration technologies.
- Knowledge of automation, CI/CD pipelines, infrastructure-as-code, and reusable engineering frameworks.
- Ability to establish engineering standards, governance, and best practices for AI systems.
- Ability to collaborate with data scientists, data engineers, architects, and business stakeholders.
- Experience monitoring, troubleshooting, and optimizing scalable AI systems and infrastructure.
Categories
About Henkel AG & Co. KGaA
Henkel AG & Co. KGaA manufactures and sells products across two divisions: Adhesive Technologies for industrial customers and Consumer Brands for households and salons. It supplies adhesives, sealants, and surface treatments to sectors such as automotive, electronics, and packaging, and markets laundry, home care, and hair care lines under brands including Persil, Schwarzkopf, and Loctite. Founded in 1876 and headquartered in Düsseldorf, Germany, it is publicly traded in Frankfurt.