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Multibank Group

Global regulated derivatives provider and exchange

Senior Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeDubai - United Arab EmiratesIn-person

About the Job

Requirements

  • Seven to 15 or more years of experience in software engineering, data science, or machine learning engineering.
  • A proven track record of building production-grade artificial intelligence systems, rather than solely notebooks or proof-of-concept work.
  • Experience owning systems end-to-end from data through model, deployment, and monitoring.
  • Advanced Python engineering skills with strong systems thinking and a focus on production quality.
  • Experience with fast iteration cycles and deploying models into live environments.
  • Ability to work directly and confidently with stakeholders and product owners.
  • Experience with PyTorch, TensorFlow, XGBoost, LightGBM, Hugging Face Transformers, Hugging Face Datasets, Hugging Face Diffusers, OpenAI application programming interfaces, Anthropic application programming interfaces, LangChain, LlamaIndex, retrieval-augmented generation architectures, vector databases, retrieval pipelines, embedding models, Pinecone, Weaviate, Milvus, FAISS, LoRA, PEFT, RAGAS, Docker, Kubernetes, MLflow, Weights and Biases, Airflow, Dagster, Prefect, GitHub Actions, GitLab CI, Evidently AI, Arize, Amazon Web Services, SageMaker, Elastic Kubernetes Service, Amazon S3, AWS Lambda, Azure Machine Learning, Azure Databricks, Google Cloud Platform, Databricks, Spark, PySpark, Delta Lake, Apache Iceberg, and lakehouse architectures.

Responsibilities

  • Architect and implement robust machine learning systems in production environments, ensuring scalability, reliability, and performance from day one.
  • Build and deploy supervised, unsupervised, deep learning, and generative artificial intelligence models into live production environments at scale.
  • Own the technical design for machine learning pipelines, feature stores, training infrastructure, and inference systems, balancing performance, cost, and maintainability.
  • Design and deliver retrieval-augmented generation systems, fine-tuning pipelines, prompt engineering frameworks, and evaluation pipelines for production-grade large language model applications.
  • Implement and maintain continuous integration and continuous delivery for machine learning, 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 artificial intelligence solutions.
  • Mentor junior and mid-level machine learning engineers, establish best practices, and contribute to technical standards across the team.
  • Contribute to strategic decisions around data architecture, artificial intelligence infrastructure, and cloud platform direction.
  • Work with mobile attribution and customer engagement data sources including Adjust, MoEngage, and Firebase for machine learning use cases such as churn prediction, personalization, and campaign optimization.

Desired Qualifications

  • Strong background in product companies, scale-ups, or enterprise AI platforms.
  • Fintech or financial services experience is an advantage.
  • Performance-based incentives are offered.

About the Company

Multibank Group

Global regulated derivatives provider and exchange

MultiBank Group delivers regulated global trading and asset tokenization across forex, metals, commodities, indices, shares, crypto, and real-world assets. Its four- pillar model includes MultiBank TradFi (20,000 instruments via MT4/MT5/MBG-Plus), MEX Exchange (institutional FX and crypto ECN), mb.io (multi‑jurisdictional crypto exchange), and mb.io RWA (tokenizing real-world assets starting with a USD 3 billion real estate deal and targeting USD 10 billion). It differentiates itself through a broad regulatory footprint with licenses from 18 authorities across five continents, plus a large physical presence in 26 countries, and an ecosystem powered by the MBG token with assets approaching USD 29 billion. The goal is to broaden access to a wide range of regulated financial instruments and scale real-world asset tokenization while prioritizing client protection and compliance.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Southern District, Hong Kong
Founded
2005

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