Lead MLOPs Engineer

The bank is transforming into an AI-led bank, revolutionizing how we serve our customers and drive the future of finance. We leverage our rich heritage and expertise to build a data-driven powerhouse that anticipates customer needs, personalizes experiences, and optimizes operations. We're not just talking about AI; we're deploying it, and we're seeing tangible results that touch the lives of every Egyptian. Join our agile, hybrid team and be at the forefront of this exciting transformation!

About the Role: We're looking for a highly experienced and strategic Lead MLOps Engineer to lead our growing MLOPs Practice. You will be a technical leader responsible for defining and implementing the MLOps strategy, building and maintaining robust machine learning pipelines, and ensuring the smooth and efficient deployment of AI models into production. Our commitment to agility, human-centricity, social inclusion, and digital transformation guides our strategic vision.

Responsibilities:

· Define and implement the technical MLOps strategy and roadmap for the bank.

· Serve as a technical leader and mentor for MLOps engineers.

· Design, build, and maintain scalable and reliable machine learning & CI/CD pipelines.

· Ensure the efficient deployment, monitoring & Governance of AI models in production.

· Collaborate with data scientists and engineers to optimize model performance and deployment.

· Establish and enforce best practices for MLOps, including version control, model governance, and monitoring.

· Evaluate and implement new MLOps tools and technologies.

Requirements:
Required Skills:

• +8 years of relevant experience in Data Science or a related field 2 years of them in the MLOps field

· Extensive experience in designing and implementing MLOps strategies and pipelines.

· Deep expertise in on-prem platforms and containerization technologies (e.g., Docker, Kubernetes).

· Strong proficiency in programming languages like Python and scripting languages.

· Experience with CI/CD & MLOps tools as well as different ML frameworks.

· Strong understanding of data engineering and software development principles.

· Excellent communication and technical documentation skills.

· Ability to work effectively in a complex and dynamic environment.

Desirable Skills:

· Experience with feature stores and model registries.

· Knowledge of data governance and compliance requirements.

• Experience with different data platforms (Cloudera, Teradata, etc..).