Job Overview

Si le interesa solicitar este empleo, por favor, asegúrese de cumplir los siguientes requisitos que se enumeran a continuación.

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

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- 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

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- 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. xcskxlj

- 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)
🏢 Ifs
📍 Madrid