Research and Development Engineer

Role overview

The National University of Singapore’s School of Computing is looking for a full-time Research Engineer to contribute to a funded, multi-year programme at the crossroads of knowledge graphs, taxonomies, ontologies, large language models, and human-AI interaction. The appointment is on site in Singapore for an initial period of 2 years, with the possibility of renewal.

The project is focused on building AI systems that function as shared language infrastructure rather than private assistants. The goal is to help interdisciplinary teams collaborate more effectively by uncovering differences in meaning, connecting experts across fields, and converting shared understanding into durable knowledge. The systems developed through this role will be used by real users and will also support publications in leading research venues.

In this position, you will serve as the main engineer translating research ideas into production-quality, testable systems while working closely with faculty members and PhD students. You will own major parts of the stack from data processing pipelines to graph and LLM back ends, as well as user-facing prototypes.

Key responsibilities

• Create scalable pipelines that process large document collections and structured datasets, then identify entities, concepts, and relationships.
• Design and tune graph-processing methods for large heterogeneous networks, including clustering, partitioning, and hierarchy building.
• Develop and maintain taxonomies and ontologies across extensive concept sets, including taxonomy induction from text and graph evidence, ontology creation and population, and cross-vocabulary matching.
• Build and support a knowledge-graph layer using property graph and/or RDF approaches, with validation and provenance management.
• Implement LLM-driven capabilities such as retrieval-augmented generation, structured extraction, multi-agent workflows, and rigorous evaluation.
• Prototype web-based tools with logging and instrumentation that can support user studies.
• Set up benchmarking, baseline systems, and evaluation pipelines while keeping the work reproducible and ready for demos.

Candidate profile

The ideal candidate should have a bachelor’s or master’s degree in Computer Science or a related discipline, along with strong Python development skills and demonstrated experience delivering systems end to end. Practical experience with LLM applications is important, including prompting, RAG, structured outputs, and evaluation.

You should also understand graph data systems such as Neo4j, RDF/SPARQL, or large-scale graph processing tools, and be familiar with taxonomies and ontologies, including concept hierarchies, is-a/subsumption reasoning, and the construction, validation, and application of structured vocabularies. A solid grounding in NLP and information retrieval is needed, especially embeddings, semantic search, and entity/relation extraction. The role also requires the ability to study technical papers and independently implement methods from them.

Preferred experience

• Advanced semantic web experience, including OWL modelling, SHACL validation, ontology matching/alignment tools such as LogMap, reasoning engines, and provenance standards like PROV-O.
• Experience with automated taxonomy induction or hypernym/subsumption extraction from corpora, or practical work with large ontologies such as Wikidata, UMLS/SNOMED, FIBO, or similar domain thesauri.
• Exposure to large-scale graph algorithms or distributed processing frameworks such as Spark, Ray, or comparable tools.
• Front-end prototyping experience with React or Streamlit, especially for instrumented study interfaces.
• Experience with multi-agent LLM systems and agent orchestration.
• Background in research labs, publications, or open-source research software.
• Interest in pursuing a PhD or MComp at the NUS Department of Computer Science, which would be a strong advantage and could serve as a pathway into graduate study.

Why this role stands out

• Work on an ambitious research vision that aims to connect people through AI rather than isolate them.
• Take ownership of a well-funded, multi-year programme with a small senior team and direct faculty mentorship.
• Contribute to systems that reach real users and support publication output at top research venues.
• Gain meaningful preparation for future PhD or MComp study at NUS.
• Use substantial compute resources to support the work.
• Receive a competitive salary aligned with experience.

Application process

Applicants are asked to send a CV, a short note describing a system they have built from end to end, and links to code or publications to the hiring team by email. Applications are reviewed on a rolling basis. NUS is an equal opportunity employer, and only shortlisted candidates will be contacted.

Additional information

This is a full-time on-site position in Singapore. The contract duration is 2 years and may be renewed. Specific project details will be shared with shortlisted candidates.