Machine Learning Engineer (Contract - For Immediate Hire)

Etihad Credit Bureau; Dubai; On-site; USD 50,000 - 75,000; Full time

Job summary

A leading financial services company in Dubai is seeking a Machine Learning Engineer to maintain scoring models and ensure high availability of production systems. The role requires strong technical skills in AzureML and Databricks, along with experience in ML operations and collaboration with data science teams. Candidates should possess problem-solving abilities and excellent communication skills to navigate between technologies and stakeholders.

Qualifications

• At least bachelor's degree or equivalent in related field.
• 2+ years experience in Data Science or Software Engineering.
• Production ML operations experience is preferred.

Responsibilities

• Monitor and troubleshoot deployed credit scoring models.
• Manage AzureML pipelines and Databricks workflows.
• Ensure 24/7 uptime of scoring APIs for clients.

Skills

Problem-solving

Communication

Organizational skills

Interpersonal skills

Education

Bachelor's or Master's in Computer Science, Engineering, Data Science, or related field

Tools

AzureML

Databricks

Python

Docker

Kubernetes

Azure Data Factory

Job description

The Machine Learning Engineer role will specialise in maintaining scoring models, production system maintenance and high-availability operations. You'll orchestrate and maintain our AzureML / Databricks-based scoring engine, ensure 99.99% uptime for production models, perform emergency fixes, and manage QA / UAT processes. This role partners with data scientists to operationalize models and data engineers to ensure efficient data flows.

KEY DUTIES & RESPONSIBILITIES

• Production Model Maintenance : Monitor, troubleshoot, and rectify issues in deployed credit scoring models (e.g., score drift, feature misalignment, output anomalies).
• Platform Orchestration : Manage AzureML pipelines & Databricks workflows for model retraining, batch scoring, and real-time inference.
• High-Availability Engineering : Ensure 24 / 7 uptime of scoring APIs serving banking clients; implement failover systems and load balancing.
• Release Management : Oversee QA / UAT processes for model updates including back-testing, shadow deployments, and canary releases.
• Model Governance : Maintain audit trails for model versions, inputs / outputs, and performance metrics. Support Compliance and Audit with creation of logs when requested.
• Incident Response : Lead troubleshooting of scoring engine failures with SLAs for financial institution clients.
• Infrastructure Optimization : Tune AzureML / Databricks clusters for cost-performance efficiency at scale.
• Vendor Management : Ensure vendor support is completing work as per scope and SLAs. Rectifying any vendor delivery issues.

EDUCATION & SKILLS

• Educated with at least bachelor’s degree or equivalent in related field
• Education specialization or master’s degree in computer science, Software Engineering
• Preferred proficiency in Arabic
• In-depth knowledge of React Native and Next JS and related modules, components and libraries
• Preferred In-depth knowledge of SiteCore or experience integrating with SiteCore

EXPERIENCE & KNOWLEDGE

• Bachelor's / Master's in Computer Science, Engineering, Data Science, or related field
• 2+ years in Data Science or Software Engineering experience
• 2+ years production ML operations experience, MLOps lifecycle management, including monitoring, retraining, and model versioning.
• Strong problem-solving skills and the ability to resolve issues efficiently.
• CI / CD for ML systems using tools such as Azure DevOps, GitHub Actions, MLflow, and other similar tools
• Ability to adapt ML workflows across different cloud environments (Azure, AWS, GCP) as needed.

ABILITIES & SPECIFIC REQUIREMENTS

• Practical experience in cloud-based ML platforms such as AzureML, Databricks, or equivalent (e.g., SageMaker, Vertex AI), with a preference for Azure.
• Python / PySpark for model debugging and patching. Working knowledge of Scikit-Learn and NumPy
• Deep understanding of credit scoring systems : feature engineering, scorecard interpretation, and output validation
• Azure Solutions Architect or MLOps certifications
• Experience with financial services-grade SLAs (99.9% uptime) and outage management
• Knowledge of containerization (Docker, Kubernetes, AKS, or similar orchestration tools)
• Practical experience with Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS) / Azure Blob Storage
• Knowledge of new and upcoming AI tools
• This is contained within the earlier requirement of python. If the plan is for this resource
• Excellent written and verbal communication skills English
• Strong interpersonal skills with the ability to engage and build relationships
• Crisis management under pressure
• Cross-functional collaboration with data science / risk teams
• Strong organizational skills with the ability to manage multiple tasks and projects simultaneously.
• Ability to develop and document procedures, roles, and guidelines.
• Security and Compliance Especially in financial services, mention data security, PII handling, and compliance with regulations

Seniority level

Seniority level

Associate

Employment type

Employment type

Contract

Job function

Job function

Information Technology

Banking and Financial Services

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