Machine Learning Engineer

ML Engineer

Role:

You will join a forward-thinking programme focused on transforming observability through AI and machine learning. This role offers the opportunity to build real-time anomaly detection models, work with modern MLOps practices, and directly impact how large-scale systems predict and prevent issues. You will gain hands-on experience with advanced AIOps use cases, operate in a highly secure environment, and contribute to a production-level transformation of monitoring capabilities.

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/Must have:

Active French Secret Clearance

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)

Benefits:

Opportunity to work on a cutting-edge AIOps transformation programme

Exposure to advanced AI, ML, and observability technologies

High-impact role with ownership of production-level solutions

Experience working in a secure, enterprise-scale environment

Salary:

Competitive day rate