Date de publication : Apr 27, 2026, 12:00AM
Orange Business is here!
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.
Deliver Reusable Capabilities: Expose AI/ML and agentic features as well-documented, reusable components that integrate seamlessly into dashboards, alerts, and operational workflows.
3-Strategy & Collaboration
Translate Business Needs into AI Use Cases: Collaborate closely with the AI lead and service-assurance stakeholders to understand operational challenges and define high-impact AI/ML projects.
Measure and Communicate Impact: Quantify the business value of your solutions (e.g., MTTR reduction, alarm noise reduction) and effectively communicate results and trade-offs to technical and non-technical partners.
Required Skills and Experience
1- Core Technical Skills
Experience : 5+ years in software and/or ML engineering, with at least 3 years of hands-on experience building and deploying production AI/ML models.
Programming : Strong proficiency in Python and its standard data science/ML libraries (e.g., Pandas, Scikit-learn, TensorFlow/PyTorch). Ability to write clean, testable, production-ready code.
Data Engineering : Solid ExperiencewithSQL and at leastonedistributed dataprocessing framework(e.g., Spark, Flink) tohandlelarge-scale datasets.
MLOps :Hands-on experience with MLOps tooling and methodologies (e.g., MLflow for versioning, CI/CD for model deployment, monitoring for drift).
2-AI/ML Expertise
Machine Learning Foundations :…