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# Senior/Lead Machine Learning Engineer

- **Company:** Ifs
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, C Sharp (Programming Language), Continuous Integration, Data Transformation, DevOps, Python (Programming Language), Machine Learning, NumPy, Tensorflow, Software Engineering, SQL Databases, AI Infrastructure, Data Processing, Feature Engineering, Pytorch, Deep Learning, Model Validation, Pandas, Containerization, Scikit Learn, Kubernetes, Information Technology, Machine Learning Operations, Terraform, Docker, Unsupervised Learning
- **Published:** August 7, 2026
- **Apply:** https://www.buscojobs.com.es/senior-lead-machine-learning-engineer-en-madrid-ID-366488671

## About the Role

This role combines software engineering, DevOps, and ML, offering impact at scale within a global, 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

## Description

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 / 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


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