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MLOps (Machine Learning Operations) Tech Lead

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Onsite

MLOps (Machine Learning Operations) Tech Lead

Henkel

MLOps (Machine Learning Operations) Tech Lead

Skills

Google Cloud PlatformSQL QueriesDockerPythonDatabricksMachine LearningAIAWSApache AirflowAzure

14 days ago

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Important information


Contract type:

Permanent

Location:

Cairo, Cairo Governorate, Egypt

Work mode:

Onsite

Published on:

7 October 2026

What they need


About this Position

Join our team and help accelerate AI adoption across the organization by building the platforms, tools, and engineering practices that power AI at scale.

What you´ll do

  • Design, build, and maintain end-to-end MLOps and AI engineering solutions, enabling efficient model development, deployment, monitoring, and lifecycle management.
  • Develop and optimize data and ML pipelines using modern cloud and orchestration technologies.
  • Implement automation, CI/CD pipelines, infrastructure-as-code, and reusable engineering frameworks to improve reliability, consistency, and time-to-market.
  • Establish and promote best practices, standards, and governance mechanisms for AI engineering and model operations.
  • Collaborate closely with data scientists, data engineers, architects, and business stakeholders to bring AI solutions from experimentation into production.
  • Monitor, troubleshoot, and continuously improve the performance, scalability, and cost efficiency of AI systems and infrastructure.
  • Evaluate and adopt emerging technologies in AI, MLOps, and cloud engineering to drive innovation and operational excellence.

What makes you a good fit

  • Bachelor's degree in Computer Science, Business informatics, STEM (Science, Technology, Engineering, and Mathematics) Majors or any relevant study
  • 5-8 years of relevant work experience
  • Passion for building scalable AI and machine learning solutions that deliver real business impact
  • Strong coding skills in Python and SQL and experience developing cloud-native data and AI applications.
  • Hands-on experience with Azure, AWS, or GCP and modern data platforms such as Databricks, Airflow, or Dagster.
  • Knowledge of MLOps best practices, including model deployment, monitoring, versioning, and lifecycle management.
  • Experience with MLflow, Spark, and other tools that enable reliable and reproducible machine learning in production.
  • Understanding of DevOps, CI/CD, Docker, and infrastructure automation principles.
  • Strong communication skills and the ability to work effectively with data scientists, engineers, and business stakeholders.

Some perks of joining Henkel

  • Flexible work scheme with flexible hours, hybrid work model, and work from anywhere policy for up to 30 days per year
  • Diverse national and international growth opportunities
  • Global wellbeing standards with health and preventive care programs
  • Gender-neutral parental leave for a minimum of 8 weeks
  • Employee Share Plan with voluntary investment and Henkel matching shares
  • Comprehensive Health Insurance for employee + dependents
  • Employee Assistance Programme provides a wide range of mental health and wellbeing benefits

At Henkel, we come from a broad range of backgrounds, perspectives, and life experiences. We believe the uniqueness of all our employees is the power in us. Become part of the team and bring your uniqueness to us! We look for a diverse team of individuals who possess different backgrounds, experiences, personalities and mindsets.

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