Machine Learning Engineer; f​/m​/d

We are seeking a skilled machine learning engineer (ML Eng) to join one of our agile development teams in our ML & AI ART.

• Develop, deploy, and optimize machine learning and AI solutions that address complex business challenges.
• Create multi‑agent systems and equip AI models with function/tool‑calling capabilities.
• Design and implement Retrieval‑Augmented Generation (RAG) systems to ground AI responses in enterprise data.
• Assess and integrate AI models (e.g., LLMs) ensuring optimal performance and reliability.
• Optimize agentic workflows and AI agents for production use cases.
• Test and optimize system prompts and few‑shot examples to ensure accurate, consistent, and safe AI outputs.
• Perform performance evaluation of machine learning and AI models using appropriate metrics, evaluation sets and techniques, and continuously iterate and improve upon them.
• Collaborate with platform teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes.
• Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions.

• Strong problem‑solving and analytical skills, with the ability to think critically and creatively about complex challenges.
• Excellent communication and collaboration skills, enabling effective teamwork with cross‑functional stakeholders at all levels of the organization.
• Ability to manage personal workloads effectively, prioritize tasks, manage timelines, and deliver high‑quality results on schedule.
• Continuous learning mindset, with a passion for staying up‑to‑date with the latest advancements in machine learning and artificial intelligence.
• Attention to detail and commitment to producing high‑quality, reliable, and maintainable code.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
• Strong programming skills in Python with experience in machine learning libraries and deep learning frameworks such as Tensor Flow or PyTorch.
• Proven experience working with Large Language Models (LLMs).
• Good understanding of AI agents & agentic workflows, LLM orchestration frameworks, and reasoning patterns.
• Experience with data preprocessing, feature engineering, and model selection and evaluation techniques.
• Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimisation.
• Understanding of software development best practices, including version control, testing, and documentation.
• Excellent problem‑solving and debugging skills, with the ability to identify and resolve issues quickly and effectively.
• Relevant work experience in machine learning, data science or a related field.
• Good English;
  Spanish is a plus.

• Continuous learning opportunities and support for professional development.
• Flexible working options.
• Wide array of health and well‑being benefits.
• Extensive career development programmes.