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.

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📌 Senior/Lead Machine Learning Engineer - Madrid, Comunidad de Madrid, Spain
🏢 Ifs
📍 Madrid