About Bull
Bull is a story. One with a century of European innovation and a working
environment where experts design powerful, sustainable, and sovereign digital
solutions, enabling states and industries to retain full control over their data
and their AI.
Bull is also thousands of engineers, researchers and passionate tech people
shaping the future of high‑performance computing, AI, and quantum technologies.
Every day, our teams push the boundaries of what is technologically possible –
from next‑generation HPC architectures to exascale supercomputers – supported by
world‑class R&D;, more than 1,600 patents, and unique end‑to‑end capabilities
spanning hardware design, software engineering, data science and quantum
research.
We are a people‑centric, innovation‑driven company, where collaboration spans
Europe, the Americas and India. We share a common vision of a responsible and
sustainable innovation that delivers concrete impact for our customers.
We are searching for a Machine Learning Engineer to join Bull’s innovative R&D;
team and contribute to the development of AI-driven solutions for infrastructure
monitoring, reliability, and cybersecurity in High-Performance Computing (HPC)
environments.
Role description:
The role focuses on leveraging large-scale operational telemetry, metrics, and
logs to build predictive capabilities that improve system availability, detect
anomalies, and support proactive operations.
The selected candidate will be responsible not only for model development but
also for rigorous validation, operationalization, and integration within a
Kubernetes-based platform.
Responsibilities:
• Design and develop ML/DL models for predicting hardware failures and detecting
software or behavioral anomalies in HPC systems.
• Apply advanced analytics techniques such as time-series forecasting, anomaly
detection, classification, and predictive maintenance using large-scale
monitoring data.
• Build and maintain data pipelines and features from infrast
📌 Machine Learning Engineer (Madrid)
🏢 Atos
📍 Madrid