Job Opportunities API

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,