Knowledge Graph Extraction Intern
SAP
Job Overview
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Job Description
About SAP
At SAP, we strive to empower our employees to bring their best, fostering an environment of continuous learning, skill growth, and strong team collaboration. We are builders, impacting over 20 industries and 80% of global commerce, and are committed to creating a workplace where you can thrive, prioritize wellbeing, and truly belong.
What You'll Build as a Knowledge Graph Extraction Intern
- Develop a proof-of-concept pipeline for automatic structured knowledge graph extraction from SAP Notes, help documentation, and system alert reports.
- Design and implement NLP and LLM-based models for entity recognition, relation extraction, and co-reference resolution, customized for SAP's unique terminology.
- Construct an evaluation framework to accurately measure the performance, completeness, and utility of the generated knowledge graphs.
- Prepare comprehensive documentation covering literature review, benchmarking results, methodology, outcomes, and potential avenues for production-level extensions.
What You Bring
- Strong foundational knowledge in Natural Language Processing (NLP), machine learning, and proficiency in Python programming.
- Practical experience with Large Language Model (LLM) fine-tuning, specifically using frameworks like Hugging Face Transformers, PyTorch, or TensorFlow.
- Familiarity with knowledge graphs, RDF, graph databases (e.g., Neo4j, Apache Jena), or other semantic web technologies.
- Robust analytical capabilities, including conducting literature reviews, benchmarking, and critically evaluating novel technical approaches.
- A keen interest in enterprise systems, technical documentation, and engaging in applied research initiatives.
- Excellent communication skills for effectively presenting research findings and collaborating with various stakeholders.
Where You Belong
This role places you within a dynamic research and development setting, dedicated to advancing enterprise knowledge management. You will join a team that excels at transforming vast amounts of unstructured text into actionable, structured knowledge. It's an environment perfectly suited for combining expertise in NLP, LLMs, and graph technologies to significantly enhance SAP's system monitoring, support mechanisms, and analytical capabilities.
Key skills/competency
- Natural Language Processing (NLP)
- Machine Learning
- Python Programming
- Large Language Models (LLMs)
- Hugging Face Transformers
- PyTorch/TensorFlow
- Knowledge Graphs
- RDF
- Graph Databases (Neo4j, Apache Jena)
- Semantic Web Technologies
- Applied Research
How to Get Hired at SAP
- Research SAP's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor to understand their commitment to innovation and employee well-being.
- Tailor your resume: Customize your application to highlight specific NLP, LLM, and graph database skills, emphasizing their relevance to enterprise knowledge management at SAP.
- Showcase project experience: Prepare a portfolio or case studies demonstrating practical application of machine learning, natural language processing, and knowledge graph construction.
- Prepare for technical deep-dives: Be ready to discuss your proficiency in Python, experience with PyTorch/TensorFlow, Hugging Face Transformers, and understanding of graph technologies like Neo4j or RDF.
- Demonstrate communication skills: Practice articulating complex technical concepts clearly and concisely, as collaboration and presentation of findings are crucial for this role at SAP.
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