Graph-Augmented RAG for Telecom at Ericsson

Massy, Ile-de-France, France -

Full Time

Start Date

Immediate

Expiry Date

19 Mar, 26

Salary

0.0

Posted On

19 Dec, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Telecommunication Systems, Network Architectures, Knowledge Representation, Document Intelligence, Retrieval-Augmented Generation, Python Programming, Data Processing, Cloud-Based AI Platforms, Graph Technologies, Generative AI, Large Language Models, Critical Thinking, Autonomy, Teamwork, Fluent English

Industry

Telecommunications

Description

Within this new lab, Standards & Technology unit, is part of Development Unit Network's global Standards & Technology organization. At Development Unit Networks, Standards & Technology secure technology leadership in Radio Access Networks (RAN) by actively driving New Concepts, Standardization, SW- and HW Research, Architecture and Testbeds. Technical focus includes 5G evolution, IoT, Digital twins, Automation / Machine Learning and Security. As a part of this new young and talented team of researchers, we are looking for motivated interns that will help us grow and engage in our activities on generative AI for telecom. Context: Telecommunication systems are defined through thousands of pages of technical specifications, standards, and white papers describing protocols, interfaces, procedures, and architectural principles. Deeply hierarchical (documents → sections → clauses → parameters) Evolving across releases and organizations Traditional Retrieval-Augmented Generation (RAG) approaches flatten the information space into independent text chunks, losing the structural hierarchy and relationships inherent in telecom documentation. Hierarchical RAG (Hi-RAG) is a new paradigm that aims to preserve and exploit document structure by combining: Hierarchical retrieval (parent/child context navigation) Graph reasoning (relations among entities) LLM generation grounded on multi-level evidence. This internship explores Hi-RAG as a foundation for telecom knowledge intelligence, bridging document structure and semantic graphs to improve factual accuracy, explainability, and reasoning depth. Research Questions: How can we represent telecom knowledge in a multi-level hierarchical-graph structure suitable for retrieval? What retrieval strategy (top-down, bottom-up, or hybrid) yields the best factual grounding? To what extent does hierarchical context reduce hallucination and improve explainability compared to standard RAG? How can the graph hierarchy be used to guide adaptive context selection under token budget constraints? Objectives: In this internship we are looking for talented students to help us to design, implement, and evaluate a Hi-RAG framework capable of understanding and reasoning over telecom domain documentation. Extract and structure telecom documents into a hierarchical format. Build a knowledge graph capturing telecom entities and their relationships. Link graph entities to document hierarchy for integrated semantic understanding. Develop a hierarchical retrieval mechanism that navigates between parent, child, and sibling sections. Combine hierarchical retrieval with LLM reasoning to create a Hierarchical RAG (Hi-RAG) system. Design prompts and context assembly methods optimized for structured, citation-based answers. Basic understanding of telecommunication systems and network architectures (4G/5G or similar). Interest in knowledge representation, document intelligence, and retrieval-augmented generation (RAG). Experience with Python programming and data processing libraries. Experience with cloud-based AI platforms, preferably AWS and Amazon Bedrock (or similar cloud LLM services). Interest in working with graph technologies (Neo4j, NetworkX, or RDF-based tools). Curiosity about Generative AI, Large Language Models, and their applications in telecom. Qualities of fast learning, critical thinking, autonomy, and teamwork. Willingness to work in an inclusive, research-oriented, and multicultural environment. Fluent English language skills in both writing and conversation. - People Services. - Process Improvement. - Cash Management. - Microsoft Office 365. - Withholding Tax. - English language. - Credit Card Applications. - Purchase Order Preparation. - Document Management. - Invoicing.

Responsibilities

The intern will design, implement, and evaluate a Hierarchical Retrieval-Augmented Generation (Hi-RAG) framework for telecom documentation. This includes extracting and structuring documents, building a knowledge graph, and developing a hierarchical retrieval mechanism.