Senior AIML Engineer – Service Assurance

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 30000 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.

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.

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: Solid understanding of ML algorithms (especially for anomaly detection classification and time-series forecasting) and the ability to choose the right tool for the job.
• Feature Engineering: Proven ability to explore diverse data sources (logs metrics events topology) assess data quality and derive meaningful features.
• Agentic AI Concepts: A strong interest in and understanding of agentic AI concepts (LLM-based agents tool-calling reasoning) and a drive to apply them to real-world operational problems.
• Observability/AIOps Platforms: Familiarity with platforms like Splunk ELK or Prometheus for analyzing logs metrics and alerts.

3-Professional & Strategic Skills

• Problem Solving & Communication: Strong analytical skills to translate complex operational problems into concrete technical solutions. Ability to communicate effectively with both technical and non-technical stakeholders.
• Education: Masters degree in Computer Science Data Science or a related field or equivalent practical experience.

Nice-to-Have Skills

• Experience with Splunk or equivalent observability tooling in a telecom/IT operations context.
• Exposure to service assurance or network operations concepts (e.g. alarms incidents SLAs topology OSS/BSS).

You bring rigor passion for challenges and determination. You seek the opportunity to expand your expertise achieve your goals and thrive.

Global Opportunities: Work in multi-national teams with opportunity to collaborate with colleagues and customers from all over the world.
Flexible Work Environment: Flexible working hours and possibility to combine work from office and home (hybrid ways of working).
Professional Development: training programs and upskilling/re-skilling opportunities.
Career Growth: Internal growth and mobility opportunities within Orange.
Caring and Daring Culture: Health and well-being programs and benefits diversity & inclusion initiatives CSR and employee connect events.
Reward Programs: Employee Referral Program Change Maker Awards.