Job Overview An ML engineer at IFS combines software engineering, DevOps, and AI/ML expertise to design and maintain scalable AI infrastructure, develop and deploy ML pipelines, and serve models at scale. Responsibilities * Design, develop, and maintain high-performance, scalable AI/ML infrastructure. * Build and execute efficient ML pipelines and serve models at scale. * Collaborate closely with data scientists, data engineers, architects, and DevOps engineers to create production-ready solutions. * Continuously monitor and improve model performance, implementing monitoring, observability, and drift detection. * Expand knowledge of AI infrastructure and share insights to guide others. Qualifications * Strong proficiency in Python and relevant libraries (NumPy, Pandas, Kserve, etc.); knowledge of additional languages like Go, C#, or SQL is a plus. * Experience with cloud platforms (Azure) and infrastructure-as-code tools (Terraform, Helm), CI/CD, GitOps (ArgoCD), and containerization (Docker,



Kubernetes). * Foundational understanding of machine learning concepts, including supervised and unsupervised learning, deep learning, and model evaluation techniques. * Proficiency in data preprocessing, feature engineering, and experience with relational and vector databases. * Excellent analytical skills and the ability to interpret complex datasets and derive actionable insights. * Excellent verbal and written communication skills, with the ability to collaborate effectively with cross‑functional teams and stakeholders. * Bachelor’s or master’s degree in Computer Science, Software Engineering, Data Science, or a related field, with at least 3+ years of software development experience, including experience with AI/ML frameworks such as TensorFlow, PyTorch, or scikit‑learn. #J-18808-Ljbffr

📌 Senior/Lead Machine Learning Engineer (Madrid)
🏢 Ifs
📍 Madrid