AI & ML Engineer

Multibank Group

1d

About The Position

This role centers on building scalable, production-grade AI systems that power real-world use cases across the business. You will develop models that directly influence customer experience, automation, and decision-making, working with modern machine learning frameworks and LLM-based technologies. Ownership spans the full lifecycle — from experimentation to deployment and continuous optimization. The focus is on delivering high-performance systems that operate reliably at scale. This is an opportunity to work on complex, high-impact problems while shaping how AI is applied in a fast-evolving, technology-driven environment.

Requirements

• Strong Python programming with ML libraries: scikit-learn, XGBoost, LightGBM TensorFlow, PyTorch Hugging Face Transformers
• Experience building and deploying models in cloud environments (AWS preferred): SageMaker Bedrock Lambda / ECS / EKS
• Strong understanding of ML algorithms (supervised, unsupervised, deep learning).
• Experience with NLP, LLMs, or time-series modeling.
• Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow Docker, Kubernetes
• Experience building real-time inference systems.
• Strong understanding of data pipelines and feature engineering.
• Ability to write production-quality, scalable code.

Responsibilities

• Design, train, and deploy machine learning models across use cases such as: recommendation systems churn prediction fraud detection behavioral scoring
• Build modular ML pipelines for feature engineering, training, validation, and inference.
• Implement deep learning and NLP models, including transformer-based architectures for text and sequence data.
• Develop and deploy LLM-based applications (e.g., summarization, chat interfaces, automation tools).
• Integrate models into production systems via REST/gRPC APIs and microservices.
• Implement MLOps pipelines using CI/CD, versioning, and monitoring tools.
• Monitor model performance, detect drift, and implement automated retraining strategies.
• Optimize models for latency, throughput, and cost in cloud environments.
• Work closely with Data Engineers to ensure scalable and efficient data access.
• Evaluate and integrate new AI frameworks and tools to continuously improve performance.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed