Senior Manager - ML Operations Platform

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About the business area

GBS is a group of highly skilled and talented professionals who form an essential part of ADCB's continued journey of success. With a proud history of commitment, innovation and delivery, GBS constantly strives for excellence whilst ensuring the highest standards of quality and risk awareness. Each and every member of the GBS family plays an integral role in driving ADCB's strategy, growth and digital evolution by working closely with our valued business partners to achieve exceptional customer experience through our outstanding service and support.

We are actively seeking an ambitious professional to join our team at ADCB to work alongside passionate colleagues who share your ambition to redefine excellence in UAE banking.

In this role, your key responsibilities include:

• Manage the design, build and operation of ML platform capabilities that enable data scientists, ML engineers and analytics teams to develop, train, deploy and serve Manage the design, build and operation of ML platform capabilities that enable data scientists, ML engineers and analytics teams to develop, train, deploy and serve models using data products from the Enterprise Data Platform (EDP).
• Ensure platform tooling, reusable pipelines, feature engineering capabilities and managed compute environments are delivered in line with approved architecture, security, governance and engineering standards to accelerate delivery of machine learning solutions.
• Manage the implementation of MLOps practices covering model training, packaging, deployment, versioning, release workflows and continuous integration and continuous delivery (CI/CD) for machine learning within approved technology and governance frameworks.
• Improve automation of model registries, retraining workflows and deployment pipelines to increase delivery consistency, reduce manual effort and support reliable movement of models from experimentation to production.
• Implement model monitoring and observability capabilities that provide visibility of model performance, data drift, concept drift, service health and production stability across deployed machine learning solutions.
• Maintain alerting, reliability patterns and remediation accelerators that support model quality, reduce operational risk and help ensure machine learning services remain dependable and fit for business use.
• Enable the use of EDP data products by translating approved data assets into reusable features, curated datasets and platform services that support prioritised analytics and ML use cases.
• Work with data owners, business subject matter experts and delivery squads to confirm enablement needs, promote reuse, reduce duplication and support delivery of measurable business value from machine learning solutions.
• Implement responsible artificial intelligence, model governance, explainability, security and auditability requirements within ML platform delivery in coordination with architecture, information security, data governance and risk stakeholders.
• Ensure platform capabilities support approved controls for model risk, personally identifiable information (PII), sensitive data handling and regulatory compliance, while tracking platform key performance indicators (KPIs) to support continuous improvement.
• Provide technical direction and day-to-day delivery guidance to ML engineers, MLOps engineers and data enablement specialists to ensure platform deliverables meet agreed quality, timeline and architectural requirements.
• Coach team members on MLOps practices, platform tooling and automation approaches, while supporting agile ceremonies, delivery planning and continuous improvement of the ML Platform function.

The ideal candidate should have the following experience: 

• At least 7 years of experience in machine learning platform engineering, Machine Learning Operations
• (MLOps), data engineering or related technology delivery within large-scale, data-driven or regulated environments.
• Bachelor’s Degree in Computer Science, Data Engineering, Artificial Intelligence, Information Systems or a related technology discipline.
• Certifications in machine learning, cloud, or data engineering, such as AWS Certified Machine Learning, Microsoft Azure AI Engineer or Azure Data Scientist, AWS Certified Solutions Architect, Databricks Machine Learning, or other equivalent industry recognised accreditations.
• ML Platform Engineering (SageMaker, Azure ML, Dataiku or Equivalent)
• MLOps and CI/CD for Machine Learning
• Model Deployment, Serving and Scaling
• Model Monitoring, Drift Detection and Observability
• Feature Engineering and Feature Store Design
• Data Product Enablement and Reuse
• Containerisation and Orchestration (Docker, Kubernetes)
• Cloud Native Architecture (AWS and/or Azure)
• Responsible AI, Model Governance and Explainability
• PII and Sensitive Data Detection
• Enterprise-Grade Solution Delivery
• Agile Delivery Practices
• Financial Services and Regulated Industry Awareness

What we offer:

Comprehensive Benefits Package: This includes market-leading medical insurance, group life and personal accident insurance, paid leave and leave airfare, employee preferential rates on loans and finance facilities, staff discounts and offers, and children education assistance (for certain job levels).

Flexible and Remote Working Options: We understand the importance of work-life balance and offer flexible working arrangements, subject to eligibility and job requirements.

Learning and Development Opportunities: We value and facilitate continuous learning and personal development, through a variety of exciting learning opportunities, such as structured instructor-led courses, a comprehensive e-Learning catalog, on-the-job training and professional development programs.

At ADCB, we are dedicated to creating a respectful, caring and disciplined work environment that aligns with your career ambitions.