AI Research Intern - Knowledge Graphs

Samsung Research UK (SRUK) is seeking exceptional and highly motivated Interns to join our growing AI team in Staines-upon-Thames. We are at the forefront of developing innovative technologies for future Samsung devices and services, and this role offers a unique opportunity to shape the next generation of mobile experiences. You will be instrumental in translating cutting-edge research into real-world impact, working on challenges that demand both creative problem-solving and robust engineering practices.,

• Architect and maintain knowledge graphs (KG), leveraging ontologies and graph databases.
• Design and implement RAG and GraphRAG pipelines to enhances reasoning for structured, contextual and dynamic data.
• Evaluate and optimize KG, RAG and GraphRAG systems for accuracy, latency and memory trade-off.
• Finetune and deploy various LLMs and adaptors for on-device applications.
• Build robust data generation and collection pipelines for model training and KG, RAG or GraphRAG construction.
• Contribute code libraries by adding new features and improving its capabilities.
• Evaluate the performance of algorithms and systems through rigorous experimentation and statistical analysis.
• Lead the development of software prototypes and experimental systems, ensuring high code quality and maintainability.
• Collaborate with a multidisciplinary team of researchers and engineers to integrate research findings into Samsung products and services.
  
  Currently studying for a PhD in Computer Science, Engineering, Mathematics or a related discipline (or just completing). Masters graduate with relevant knowledge and experience also considered.
• First-author publication in one of the following conferences and journals: NeurIPS, ICML, ICLR, EMNLP, CVPR, ICCV, ECCV, AAAI, ACL, IEEE TPAMI, IEEE TNNLS, IJCV, and JMLR.
• Deep technical expertise on Knowledge Graphs: Proficiency in RDF, SPARQL and tools like Neo4j.
• Deep technical expertise on RAG/GraphRAG: Hand-on experience with frameworks like LangChain, LLamaIndex and Vector Databases.
• Deep technical expertise on LLMs: Expertise in fine-tuning, prompt engineering and deploying HuggingFace models and vLLMs.
• Deep technical expertise on Databases: Proficiency in SQL and NoSQL systems, with optimization skills for high-volume data.
• Expert proficiency in Python programming language.
• Proficiency in Pytorch, with experience in NLP tasks.
Desirable Skills
• Expert proficiency in Java/Kotlin programming language.
• Previous hands-on experience with deep learning model optimization: quantization, pruning, distillation, or operator-level optimizations.
• Experience with deploying AI models on-device (mobile, embedded, edge accelerators, etc.).