Experteer Overview
As an ML engineer at IFS, you design and maintain scalable AI/ML infrastructure and pipelines. You collaborate with data scientists, data engineers, and DevOps to deploy production-grade AI solutions. You translate innovative AI opportunities into sustainable products while ensuring observability and drift detection. This role combines software engineering, DevOps, and ML, offering impact at scale within a global, inclusive, and innovation-driven context.

Compensaciones / Incentivos
• Design and maintain high-performance AI/ML infrastructure
• Build and run scalable ML pipelines and model serving at scale
• Develop tools for monitoring, observability, and continuous improvement
• Collaborate with data scientists, data engineers, architects, and DevOps to deploy AI-driven solutions
• Expand knowledge of AI infrastructure and domain processes to guide others

Responsabilidades
• Proficient in Python with NumPy, Pandas, and Kserve; additional languages like Go, C#, or SQL are a plus
• Familiarity with Azure cloud,



infrastructure as code (Terraform, Helm), CI/CD, GitOps with ArgoCD, and containerization (Docker, Kubernetes)
• Foundational ML concepts across supervised/unsupervised learning, deep learning, model evaluation
• Data handling skills including preprocessing and feature engineering; experience with relational and vector databases
• Strong analytical abilities to interpret complex data and derive insights
• Excellent communication skills for cross-functional collaboration
• Bachelor’s or Master’s in Computer Science, Software Engineering, Data Science, or related field with 3+ years in software development including AI/ML frameworks (TensorFlow, PyTorch, scikit-learn)

Requisitos principales
• hybrid work opportunities
• inclusive workplace experiences
• flexible work arrangements
• opportunity to work on impactful AI solutions
• global team collaboration

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