Senior Machine Learning Engineer
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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.
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Overview
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.
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