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 integral, inclusive, and innovation-driven context.Compensaciones / Beneficios
- 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 othersResponsabilidades
- 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