Summary
MultiBank Group is a global financial institution headquartered in Dubai, UAE. It is seeking a Senior Machine Learning Engineer to build and operate production ML systems, including models, pipelines, feature stores, inference systems, and LLM applications. The role also covers MLOps, monitoring, model optimization, and mentoring engineers, with use cases involving customer engagement and mobile attribution data. Applicants should have 7 to 15 or more years of relevant experience and strong Python and production engineering skills; fintech experience is an advantage.
The posting
As published on multibankgroup.com. Pulled from the employer's site and shown as they wrote it.
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
Proven track record of building production-grade AI systems, not solely notebooks or proof-of-concept work
Comfortable owning systems end-to-end from data through model through deployment through monitoring
Product-first engineering approach, not research-only profiles
Advanced Python engineering skills with strong systems thinking and a focus on production quality
Comfortable with fast iteration cycles and deploying models into live environments
Ability to work directly and confidently with stakeholders and product owners
Fintech or financial services experience is an advantage
Technical Skills
Machine Learning and AI: PyTorch, TensorFlow, XGBoost, LightGBM, Hugging Face (Transformers, Datasets, Diffusers)
LLM and GenAI: OpenAI and Anthropic APIs, LangChain, LlamaIndex; RAG architectures with vector DB and retrieval pipelines; embedding models (OpenAI, Cohere, open-source); Pinecone, Weaviate, Milvus, FAISS; fine-tuning via LoRA and PEFT frameworks; evaluation using RAGAS and custom pipelines
MLOps and Production: Docker, Kubernetes, MLflow, Weights and Biases, Airflow, Dagster, Prefect, GitHub Actions, GitLab CI, Evidently AI, Arize, custom observability stacks
Cloud: AWS (SageMaker, EKS, S3, Lambda), Azure ML, Azure Databricks, GCP
Data Stack: Databricks, Spark, PySpark, Delta Lake, Apache Iceberg, Lakehouse architectures
Why Join Us?
Work with one of the world’s leading financial derivatives institutions.
Competitive salary plus performance-based incentives.
Access to a dynamic, international, and fast-growing environment.
Strong opportunities for career progression within a global financial group.
Be part of a business committed to innovation, excellence, and long-term growth.
Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.