Atos is seeking a Machine Learning Engineer to join its R&D team in Madrid, focusing on developing AI-driven solutions for high-performance computing environments. The role emphasizes model development, predictive analytics, and operationalization within a Kubernetes-based framework
Job Summary
Leverage large-scale operational telemetry, metrics, and logs to build predictive capabilities that improve system availability, detect anomalies, and support proactive operations.
Design and develop ML/DL models for predicting hardware failures and detecting software or behavioral anomalies in HPC systems, and deploy/operationalize models within a Kubernetes-based environment.
Flexible Work Schedule with half day Fridays and an intensive summer workday, plus opportunities to work with advanced AI technologies in an innovative and supportive R&D environment.
Matching Summary
Match Score: 85
Atos is seeking a Machine Learning Engineer to join its R&D team in Madrid, focusing on developing AI-driven solutions for high-performance computing environments. The role emphasizes model development, predictive analytics, and operationalization within a Kubernetes-based framework.
Skills & Requirements
Must-have
Machine Learning and Deep Learning frameworks
Time-series data and anomaly detection
Python and data science ecosystems
Kubernetes-based environment deployment
Production-grade ML pipelines
Large-scale monitoring datasets
Nice-to-have
HPC environments, GPUs, and high-speed interconnects
Agile/Scrum environment collaboration
AI-driven cybersecurity use cases
Key Requirements
Master’s or PhD in Computer Science, AI, Data Science, Telecommunications
Experience with Prometheus or similar monitoring systems