Build and maintain scalable and efficient machine learning pipelines for data preprocessing, model training, and evaluation;
Deploy and monitor machine learning models in production environments, ensuring high performance and reliability;
Integrate Large Language Models (LLMs) and Vision Language Models (VLMs) into existing applications to enhance functionality and create new AI-enhanced features;
Develop and implement Retrieval Augmented Generation (RAG) systems for knowledge-intensive applications;
Design and build LLM-based AI agents for automation, customer support, and other interactive applications;
Experiment with and evaluate different LLM techniques, including fine-tuning, prompt engineering, and embedding generation;
Develop and maintain clear and concise documentation for models, pipelines, and APIs;
Participate in code reviews and contribute to best practices for AI development;
Monitor and analyze model performance in production, identifying areas for improvement and optimization;
research and stay up to date on the newest AI trends;
Ensuring that all activities and duties are carried out in full compliance with regulatory requirements and supporting the continued implementation of the Group Anti-Bribery and Corruption Policy.

University degree in Computer Science, Engineering, or a relevant discipline;
4+ years of experience in developing AI/GenAI solutions and deploying machine learning models in production environments;
Strong understanding of traditional machine learning algorithms and techniques (e.g., linear regression, logistic regression, decision trees, support vector machines, clustering);
Experience with AI services, including Azure OpenAI, Azure AI Search, and Azure Machine Learning, for building and deploying intelligent applications is highly desirable;
Proficiency in programming languages such as Python, and experience with machine learning libraries like scikit-learn, TensorFlow, or PyTorch;
Experience with natural language processing (NLP) and computer vision (CV) techniques;
Experience with building and deploying AI agents;
Experience with building and deploying API's;
A proactive and self-motivated approach to work;
A strong attention to detail and a commitment to quality;
Ability to work effectively in a fast-paced and collaborative environment;
A strong desire to learn;
Excellent written and verbal communication skills;
Experience and willingness to work in an international/multicultural environment;
Excellent knowledge of English language (written and verbal).

ML Engineer

Key skills