Arbetsbeskrivning

Ericsson AB

About this opportunity:

We are looking for a Master’s graduate with a strong AI/ML background to join our RAN OAM Management team as a System Developer. You’ll work at the frontier of agentic AI, autonomous networks and data engineering – turning raw RAN data into intelligent agents and autonomous functions on live networks.

You will join a team of 16 experts owning the RAN OAM system architecture, defining how operators monitor, configure and automate their RAN, and evolving it toward autonomous, AI-driven, self-healing and self-optimizing networks. Previous team members have grown into system architect and technical leadership roles. You won’t just build models or pipelines – you’ll help design the “data nervous system” and agent systems that perceive and act on one of the world’s most complex distributed infrastructures.

What you will do:

• Build and systemize end-to-end AI/ML solutions for RAN operations – from raw network data and feature engineering to models and agents that act on live networks (RAN features, rApps, OAM functions).
• Design data pipelines and data quality guards that turn heterogeneous RAN/OAM data into reliable, agent-ready and ML-ready datasets.
• Develop ML/DL models (e.g. time-series forecasting, anomaly detection, root-cause analysis) with solid MLOps (training pipelines, monitoring, drift detection, CI/CD).
• Contribute to agentic AI for network operations (LLM-based agents, tool use/function calling, multi-agent coordination, human-in-the-loop).
• Collaborate with RAN/OAM experts to turn operational workflows into autonomous use cases with clear autonomy maturity targets.

The skills you bring:

• Master’s degree in Computer Science, Electrical Engineering, Engineering Physics, Data Science, or similar (recent graduate).
• Strong ML/AI fundamentals (supervised, unsupervised and reinforcement learning).
• Experience with time-series forecasting, anomaly detection or root-cause analysis on operational or sensor data.
• Proficiency in Python and common ML/DL frameworks.
• Understanding of MLOps basics - training pipelines, monitoring, drift detection and CI/CD for ML.
• Interest in agentic AI concepts (LLM-based agents, tool use/function calling, prompt engineering).

Good to have:

• Experience designing data pipelines for high-volume data (batch and/or streaming).
• Familiarity with data quality and observability (schema validation, data contracts, lineage tracking).
• Experience with distributed data processing (e.g. Spark, Dask, Ray or similar).
• Telecom domain knowledge or familiarity with Ericsson platforms and autonomous networks frameworks is a plus.