Senior Machine Learning Engineer

About the role

Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.

Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.

Role Overview

We are seeking a Senior Machine Learning Engineer to join our AI team as a technical owner of ML products and infrastructure. This is a deeply hands-on engineering position for someone who builds and scales production AI systems used by real users in real-time environments. The right candidate operates across the full ML lifecycle — from model design through deployment, optimization, and ongoing performance in production — and contributes to the technical direction of the AI platform.

Key Responsibilities

- Architect and implement robust ML systems in production environments, ensuring scalability, reliability, and performance from day one

- Build and deploy supervised, unsupervised, deep learning, and generative AI models into live production environments at scale

- Own technical design for ML pipelines, feature stores, training infrastructure, and inference systems, driving decisions that balance performance, cost, and maintainability

- Design and deliver RAG systems, fine-tuning pipelines, prompt engineering frameworks, and evaluation pipelines for production-grade LLM applications

- Implement and maintain CI/CD for ML, model versioning, monitoring, drift detection, and automated retraining pipelines

- Continuously optimize model performance, inference latency, cost efficiency, and reliability across live systems

- Collaborate with product managers, engineers, and data teams to translate business problems into scalable, maintainable AI solutions

- Mentor junior and mid-level ML engineers, establish best practices, and contribute to technical standards across the team

- Contribute to strategic decisions around data architecture, AI infrastructure, and cloud platform direction

- Work with mobile attribution and customer engagement data sources including Adjust, MoEngage, and Firebase for ML use cases such as churn prediction, personalization, and campaign optimization

Requirements

- 7 to 15 or more years of experience in software engineering, data science, or ML engineering

- Strong background in product companies, scale-ups, or enterprise AI platforms