AI/ML Engineer
Posted 14 Oct 2026
Advertised as “Senior AI/ML Engineer – Service Assurance”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- Individual contributor
- Employment
- Hybrid
No salary listed for this role.
Field of studyComputer Science, Data Science (or related)
Study levelMaster's
Publication date : Apr 27, 2026, 12:00AM
About us
Join us at Orange Business!
We are a network and digital integrator that understands the entire value chain of the digital world, freeing our customers to focus on the strategic initiatives that shape their business.
Every day, you will collaborate with a team dedicated to providing consistent, sustainable global solutions, no matter where our customers operate. With over 30,000 employees across Asia, the Americas, Africa, and Europe, we offer a dynamic environment to develop and perfect your skills in a field filled with exciting challenges and opportunities.
About the role
As a Senior AI/ML Engineer, you will be at the heart of transforming our Service Assurance capabilities.
Your mission will include (and not be limited to) leverage cutting-edge AI to predict and prevent service disruptions, automate root cause analysis, and ensure our network runs with unparalleled reliability.
You will be responsible for exploring service and network data, designing and implementing AI/ML and agentic capabilities on top of Splunk and Ciena Blue Planet UAA, and industrializing these solutions into production-grade features.
This role combines hands-on data exploration, model development, and solid software engineering to deliver advanced analytics for anomaly detection, event correlation, root cause analysis, and forecasting.
About you
Key Responsibilities
1-Core Model Development & Innovation
- Design and Implement AI/ML Solutions:Own the end-to-end lifecycle of AI/ML models for service assurance, covering anomaly detection, event correlation, root cause analysis, and capacity/traffic forecasting.
This includes data discovery, feature engineering, model training, evaluation, and deployment. - Prototype and Industrialize Agentic AI:Explore and build next-generation operational tools, such as LLM-based copilots for triage, agents that reason over telemetry and topology, and natural-language interfaces for observability data.
- Stay at the Forefront of AIOps:Continuously research advances in ML for observability, proactively prototyping and industrializing innovative ideas that enhance our service-assurance capabilities.
2-Engineering & MLOps Excellence
- Build Scalable Data Pipelines:Engineer and maintain robust pipelines to ingest, transform, and prepare high-volume observability data (metrics, logs, alarms, tickets, topology) for AI/ML workloads.
- Implement MLOps Best Practices:Ensure our solutions are production-grade by implementing model versioning, automated testing, CI/CD for ML, and continuous monitoring for data and model drift.