AIOps ML Engineer: Real‑Time Anomaly Detection & Observability

Hamilton Barnes ?; Toulouse; On-site; EUR 50,000 - 70,000; Full time

Job summary

A technology consulting firm in Toulouse is seeking a Machine Learning Engineer to join a forward-thinking program focused on transforming observability through AI and machine learning. You will build and deploy machine learning models for real-time anomaly detection, support AI integrations into the ELK stack, and work within MLOps principles. The role offers hands-on experience in a highly secure environment and a chance to impact production-level monitoring capabilities significantly.

Qualifications

• Strong experience in Machine Learning, particularly anomaly detection or time-series analysis.
• Hands-on experience with Python or similar for ML development.
• Experience deploying models into production environments.
• Understanding of MLOps principles and tools.
• Experience with ELK Stack (Elasticsearch, Logstash, Kibana).

Responsibilities

• Build and deploy machine learning models for anomaly detection and alert correlation.
• Transition monitoring from static thresholds to real-time intelligent detection.
• Support the integration of AI capabilities into the ELK stack.
• Work within an MLOps framework to manage, monitor, and improve models.
• Contribute to automated alert prioritisation and multi-source correlation.

Skills

Machine Learning

Anomaly Detection

Python

MLOps

ELK Stack

Job description

A technology consulting firm in Toulouse is seeking a Machine Learning Engineer to join a forward-thinking program focused on transforming observability through AI and machine learning. You will build and deploy machine learning models for real-time anomaly detection, support AI integrations into the ELK stack, and work within MLOps principles. The role offers hands-on experience in a highly secure environment and a chance to impact production-level monitoring capabilities significantly.